Ant traits, myrmecophiles, and disturbance

James Glasier Evolution and Ecology Research Centre School of Biological, Earth and Environmental Sciences University of New South Wales

August 2017

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name: Glasier First name: James Other name/s Abbreviation for degree as given in the University calendar: PhD School: School of Biological, Earth and Environmental Sciences Faculty: Science Title: Ant traits, myrmecophiles, and disturbance Abstract 350 words maximum (PLEASE TYPE) Ants are eusocial insects that are diverse, abundant, and globally widespread. These attributes allow ants to play an important role in terrestrial ecosystems; such as significantly contributing to soil turnover, predator-prey relationships, and facilitating biodiversity. This thesis examines how environmental factors and species traits, play a role in determining symbiotic relationships, as well as determining resilience to disturbance. Chapter 1 looks at why ants are good focal taxa to study a wide range of ecological questions including symbiotic associations, climatic influence in species richness, and habitat disturbance on communities. Chapters 2, 3, and 4 involved a database of ants and myrmecophiles, synthesized by me from 351 references, that included 622 ants and 1629 myrmecophiles. In Chapter 2, I examined if the global species richness of myrmecophiles and their symbiotic relationships, was determined by regional ant species richness or climatic variables associated with a latitudinal gradient. I found that both ant species richness and climatic variables influenced myrmecophile richness, but richness of symbiotic relationships were more affected by climatic variables. In Chapter 3, I looked at ant traits such as colony size, diet or morphological traits and determined which were correlated with more myrmecophile associations. I found that large colony size (>1000 000) and number of spines, played an important role in explaining the number of myrmecophiles associated with an ant. Chapter 4 models the host range of different myrmecophile relationships at the species level, contrasting relationship type and taxonomic group to determine if myrmecophiles with beneficial or detrimental relationships have more hosts. I found that beneficial relationships had a higher number of associations compared to detrimental ones. For Chapter 5, I did a field study looking at the effects of grazing intensity and history on below- and aboveground ant communities within the arid woodlands of New South Wales. I found that below-ground communities were resilient to grazing disturbance, and that grazing history had a great er affect on above-ground communities than grazing intensity. Chapter 6 summarizes my findings, discusses the implications of my work, the limi tations of the studies, and suggests future paths of research on ants and myrmecophiles.

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ii Abstract

Ants (Family Formicidae) are eusocial insects that are diverse, abundant, and globally widespread. These attributes allow ants to play an important role in terrestrial ecosystems; such as significantly contributing to soil turnover, nutrient cycling, predator-prey relationships, and facilitating biodiversity, through close associations with other organisms. This thesis examines how environmental factors and species traits, play a role in determining these species associations, as well as determining resilience to disturbance. Chapter One looks at why ants are a good focal taxon to study a wide range of ecological questions including symbiotic associations, climatic influence in species richness, and habitat disturbance on communities. Chapters Two,

Three, and Four involved a database of ants and their myrmecophiles (organisms associated with ants), synthesized by me from 351 references, that included 622 ant and 1629 myrmecophile species. In Chapter Two, I examined if the global species richness of myrmecophiles (organisms that capitalize on the social fabric of ant biology) and their symbiotic relationships (mutualisms, commensalisms, kleptoparasitisms, and parasitisms), was determined by regional ant species richness or climatic variables associated by the common latitudinal gradient (for example: average annual temperature, precipitation, and net primary productivity). I found that both ant species richness and climatic variables were important for overall myrmecophile species richness, but for the symbiotic relationships, climate had greater effect on species richness overall. In Chapter Three, I look at species specific ant traits such as colony size, diet or morphological traits such as number of spines or functional stingers, and determined which traits were correlated with more myrmecophile associations. I found that large colony size (>1000 000), number of

iii spines and diet, played an important role in explaining the number of myrmecophiles associated with an ant. Chapter Four models the host range of different myrmecophile relationships at the species level, contrasting relationship type and taxonomic group to determine if myrmecophiles with beneficial or detrimental relationships interact with more hosts. I found that beneficial relationships, and taxa that were involved in these relationships had a higher number of associations compared to detrimental ones. For

Chapter Five, I did a field study looking at the effects of grazing intensity and history on below- and aboveground ant communities within the arid woodlands of New South

Wales. I found that below-ground communities were resilient to grazing disturbance, and that grazing history had a greater affect on above-ground communities than grazing intensity. My last chapter, Chapter 6 summarizes my findings, discusses the implications of my work, the limitations of the studies, and suggests future paths of research on ants and myrmecophiles.

iv Acknowledgments

First, I would like thank my supervisor David Eldridge for all his advice and guidance throughout the course of this research. Thank you for giving me the opportunity to do this work and assist me in studying ants! I am also thankful to Alistair Poore for his advice in research structure and statistical design. Thank you to the Examiners for thoughtful and helpful comments.

I would like to thank Max Mallen-Cooper, Marta Ruiz Colmenero, and Samantha

Travers for help with fieldwork. Thank you to Derek Smith from the Australian

Museum who assisted with ant identification.

Thank you to my friends: Steph Brodie, Chris Setio, Len Martin, and Charlotte Mills for their support, frienship, and guiding me through Australian culture. Steph Brodie, I doubly thank you for all your help with stats, advice, and coffees.

This research would not be possible without the University International Postgraduate Award from the University of New South Wales for funding.

Thank you to my friends and family, with out them this thesis would have never been possible. To my mother, Linda Glasier, thank you for your unwavering support, direction, and love. To Melissa Baron, your unconditional support, understanding, and love provided a bedrock for me to do this PhD, love you!

Lastly, Ants are Awesome.

v

Table of Contents

Abstract ...... iii Acknowledgments ...... v Table of Contents ...... vi List of Figures...... x List of Tables ...... xii Chapter 1 ...... 1

1.1 Background ...... 1

1.1.1 Ants as a focal taxon...... 1 1.1.2 Ants and the environment ...... 2 1.1.3 Ants and disturbance...... 3 1.1.4 Ant ecology ...... 4 1.2 Research Objectives ...... 7

1.3 Thesis Structure ...... 8

Chapter 2 ...... 11

Climate or host richness: what drives global myrmecophile species richness? ...... 11 2.1 Abstract ...... 11

2.2 Introduction ...... 12

2.3 Methods ...... 16

2.3.1 Data collection ...... 16 2.3.2 Definitions ...... 17 2.3.3 Global richness ...... 19 2.3.4 Statistical analysis ...... 19 2.4 Results ...... 21

2.4.1 General results...... 21 2.4.2 Overall myrmecophile richness ...... 27 2.4.3 Mutualist species richness...... 27 2.4.4 Commensal species richness ...... 30 2.4.5 Kleptoparasite species richness ...... 30

vi 2.4.6 Parasite species richness ...... 31 2.5 Discussion...... 31

2.5.1 Overall myrmecophile richness ...... 31 2.5.2 The richness of mutualist myrmecophiles shows no latitudinal gradient 32 2.5.3 Commensals and the importance of ant apecies richness...... 33 2.5.4 Kleptoparasites: climate and resource stability ...... 34 2.5.5 Parasites: seasonality and the need of reliable hosts ...... 35 2.5.6 Conclusion ...... 37 Chapter 3 ...... 39

Ant traits determine richness of myrmecophiles associated with individual ant species ...... 39 3.1 Abstract ...... 39

3.2 Introduction ...... 40

3.3 Methods ...... 45

3.3.1 Data collection ...... 45 3.3.2 Ant and trait definitions ...... 46 3.3.3 Myrmecophile relationship definitions ...... 48 3.3.4 Statistical analyses...... 49 3.4 Results ...... 50

3.4.1 General results...... 50 3.4.2 Differences in myrmecophile rchness between subfamilies ...... 52 3.4.3 Predicting myrmecophile richness from ant traits...... 55 3.4.4 Variation in importance of ant traits among differing symbiotic relationships ...... 55 3.5 Discussion...... 61

3.5.1 Ant traits are strong predictors of myrmecophile richness ...... 61 3.5.2 A few ant subfamilies rich in myrmecophiles ...... 64 3.5.3 Parasite enigma ...... 65 3.5.4 Conclusion ...... 65 Chapter 4 ...... 67

Do mutualistic associations have broader host ranges than neutral or antagonistic associations? A test using myrmecophiles as model organisms ...... 67 4.1 Abstract ...... 67

vii 4.2 Introduction ...... 68

4.3 Methods ...... 71

4.3.1 Data compilation ...... 71 4.3.2 Contrasts in host range among myrmecophile taxa, reliance and relationship types ...... 73 4.4 Results ...... 75

4.4.1 The distribution of myrmecophiles among invertebrate taxa and relationship types ...... 75 4.4.2 Contrasts of host range among myrmecophile taxa, dependence and relationships ...... 76 4.5 Discussion...... 82

4.5.1 Host range of myrmecophile orders ...... 83 4.5.2 Host range of dependence and relationship types ...... 85 Chapter 5 ...... 89

Variable effects of current and historic livestock grazing on above- and below- ground ant communities in a wooded dryland ...... 89 5.1 Abstract ...... 89

5.2 Introduction ...... 90

5.3 Methods ...... 93

5.3.1 The study area ...... 93 5.3.2 Ant and ground cover sampling ...... 95 5.3.3 Statistical methods ...... 97 5.4 Results ...... 99

5.4.1 Ant species richness ...... 99 5.4.2 Ant community composition ...... 102 5.4.3 Grazing and environmental effects on ant species richness...... 105 5.5 Discussion...... 108

5.5.1 Grazing effects on ant community structure ...... 108 5.5.2 Drivers of ant community structure ...... 112 5.5.3 Concluding remarks ...... 114 Chapter 6 ...... 115

viii Conclusion: Ecology of ant and myrmecophile ...... 115 6.1 General Discussion ...... 115

6.2 Future Directions ...... 119

References ...... 122 Appendix A ...... 141 Appendix B ...... 164 Appendix C ...... 166 Appendix D ...... 167 Appendix E...... 168 Appendix F ...... 171 Appendix G ...... 172

ix List of Figures

Figure 1.1 Conceptual model showing effects of environment, disturbance, and myrmecophiles on ants. Black arrows represent conceptual strength of interactions. Numbers and dashed arrows represent the chapters of this thesis, and the interactions that are discussed within a chapter...... 8 Figure 2.1 Modelled relationships between global myrmecophile species richness and highly influential variables. a) number of sites, b) absolute latitude (i.e., degrees from the equator), c) ant species richness, d) mean annual temperature, e) temperature variation, f) annual precipitation and g) net primary productivity. Variables c) to g) were all found to be in the best model to explain global myrmecophile species richness. Lines are calculated using the ‘visreg’ function in R (Breheny & Burchett 2013), with 95% confidence intervals. Models b) to g) are corrected for number of sites sampled within a 2° grid...... 24 Figure 2.2 Global myrmecophile species richness in 2° by 2° grids. Larger and lighter coloured circles represent higher species richness. Each point represents the middle of the 2° by 2° grids...... 26 Figure 2.3 Variation in global species richness per 2° grid of myrmecophile relationships with absolute latitude (i.e., degrees from the equator). Lines represent fit models using the visreg function in R (Breheny and Burchett 2013), with 95% confidence intervals. Models are absolute latitude corrected for number of sites sampled at that latitude. (*) indicates a significant effect (P< 0.05) of latitude on myrmecophile species richness...... 28 Figure 2.4 Model average coefficients and Relative Variable Importance (RVI) of predictor variables for species richness of all myrmecophiles and myrmecophile relationship-types. Error bars represent 95% confidence intervals. Variables are listed according to rank by RVI for each modelled group...... 29 Figure 3.1 Modelled relationships between myrmecophile richness and highly influential variables. a) The relationship between myrmecophile richness and number of references per ant species supporting the need to use references as an offset in further analyses; b) The variation in myrmecophile richness with ant colony size (levels that share a letters do not differ in Tukey’s post-hoc analysis. c) The relationship between the number of pairs of spines and myrmecophile richness. Both a) and c) represent fitted models visualled using the visreg function in R (Breheny and Burchett 2013), with the dotted lines representing 95% confidence intervals...... 53 Figure 3.2 Average Myrmecophile richness per ant species within different Formicidae subfamilies, paired with the Formicidae phylogeny based on Moreau et al. 2006, Brady et al. 2006, & Ward et al. 2007. Data are modelled estimates and error bars are 95% confidence intervals from a generalized linear model contrasting myrmecophile associations and ant subfamilies, with a statistical offset of number of references per species. Dot points indicate average myrmecophile richness per ant host. Subfamilies that share a letter do not differ in Tukey’s post-hoc analysis...... 54 Figure 3.3 Relative Variable Importance (RVI) of predictor variables for number of myrmecophile associations per ant species. Variables are listed according to rank by RVI for each modelled group. The dotted line indicates 0.70 RVI the weighting used to indicate an influential variable...... 57

x Figure 3.4 Modelled interactions of myrmecophile species per ant and highly influential variables. a) is the relationship between mutualist richness and ant spine pair; b) shows the differences of mutualist richness and if an ant has a functional sting or not. c) represents ant colony size and commensal richness; d) is the relationship between pairs of ant spines and commensal richness; e) represents the differences between ant subfamilies and commensal richness; f) represents difference in ant colony size and richness of kleptoparasites; g) shows the difference of kleptoparasite richness between ants with and without a sting h) represents the differences between ants within different subfamilies and kleptoparasite richness. a) to h) represent fit models using the visreg function in R(Breheny & Burchett 2013), with 95% confidence intervals. Letters denote significance (P<0.05)...... 60 Figure 4.1 The number of myrmecophile species exhibiting different degrees of reliance on their ant hosts and type of relationships with ants...... 76 Figure 4.2 The distribution of host breadth (number of ant species) for all species of myrmecophile...... 7 9 Figure 4.3 The number of host ant species per myrmecophile species for the five most speciose orders of myrmecophiles. Note: Data are estimates and 95% confidence intervals from a generalized linear model contrasting host range across orders. Sample sizes (numbers of myrmecophile species) are given above the x-axis...... 80 Figure 4.4 Differences in the number of host ant species per myrmecophile species between facultative and obligate interactions...... 81 Figure 4.5 Differences in the number of host ant species per myrmecophile species among mutualistic, commensal, kleptoparasitic and parasitic interaction types...... 82 Figure 5.1 Ant species richness in relation to three levels of historic livestock grazing for aboveground and belowground ant communities. For aboveground ants, different letters indicate a significant difference among grazing levels for above-ground species at P < 0.05. There were no significant differences for belowground ant communities...... 100 Figure 5.2 Comparison of above and below ground ant species richness with distance from water. Fig. A represents changes in mean species richness in three different grazing histories (long ungrazed, recently ungrazed, currently grazed) along a decreasing grazing intensity gradient (declining with increased distance). Fig. B shows average (± 95% CI) change of aboveground and belowground ant species richness between all samples in relation to increasing distance from water (declining grazing intensity). There were no significance between richness and grazing intensity (P > 0.05, Appendix F)...... 101 Figure 5.3 Mean (± 95% CI) species richness of the five most speciose ant functional groups with increasing distance from water, summed over above-ground richness. Models for the Dominant Dolichoderinae and Hot Climate Specialists were significant for diversity change with distance from water (P < 0.05; Appendix F)...... 102 Figure 5.4 Structural equation models for (A) aboveground and (B) belowground ant species richness in relation to time since grazing (grazing history) and intensity (distance from water) and the cover of biocrusts, litter, bare soil and plants. Histograms indicate the standardised total effects (STEs) for the six attributes. Standardized path coefficients, embedded within the arrows, are analogous to partial correlation coefficients, and indicate the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of

xi arrows is proportional to the strength of path coefficients. The proportion of variance explained (R2) is shown for each attribute. Only significant pathways are shown in the models. Model fit: χ2 = 2.19, df = 4, P = 0.701. History = historic grazing (time since grazing), Intensity = grazing intensity (distance from water)...... 107

List of Tables

Table 2.1 The orders of invertebrates that are known myrmecophiles, with the number of species and families of myrmecophiles per order, and the number of species for each type of relationship the myrmecophile has with ants...... 23 Table 2.2 Comparison of best-performing models effecting myrmecophile and relationship-type species richness. Each row contains the intercept and parameter coefficients that comprised a single model, along with the number of parameters (K), corrected Akaike’s Information Criteria (AICc); change in AIC from best model (ΔAIC); Akaike Weights (wi). Best ranked model for each group is bolded...... 25 Table 3.1 The number of ant species, myrmecophiles and the average myrmecophile richness for each subfamily of ant recorded in our study. The modelled average was determined using negative binomial generalized linear model with number of references per ant as a statistical offset...... 51 Table 3.2 Candidate models using ant traits to predict myrmecophile species richness per species. Models for each mycophile relationship are also presented. Each row contains model variables, number of parameters (K), corrected Akaike Information Criterion (AICc), change in AIC (ΔAIC) from best model, and Akaike weights (wi). Number of references was used as statistical offset in each model. The Null model includes the statistical offset (number of references)...... 56 Table 4.1 The orders of invertebrates that are known myrmecophiles, with the number of species and families of myrmecophiles per order, the number of species for each type of interaction, and the number of references per order...... 78 Table 5.1 Ant species indicative of different grazing histories (time since grazing) for aboveground and belowground samples. Functional groups based on Andersen (1995)...... 104 Table 5.2 SEM coefficients for the relationships between grazing history (time since grazing) and intensity (distance from water), bare soil cover, plant cover and litter cover and total aboveground and belowground ant richness and richness of five functional groups. Only significant SEM coefficients are shown...... 105

xii Chapter 1

1.1 Background

1.1.1 Ants as a focal taxon

The use of focal taxa is a valuable tool for ecologists. Comprehensive surveys of all taxa within an area is often impractical, and therefore it is advantageous to focus on taxa that are diverse, widespread, abundant, easily sampled, and indicators of other taxonomic diversity (Oliver et al. 1998; Ellison 2012). Furthermore, focal taxa can be used to model ecological questions dealing with diversity patterns, symbiotic associations, and disturbance. Even when focal taxa patterns do not correlate with other organisms, using a singular taxon can lead to better understanding of its natural history, knowledge of evolutionary processes, and understanding changes in biodiversity patterns (Agosti et al. 2000).

Globally, ants (Family: Formicidae), are one of the most conspicuous terrestrial invertebrates. They are found on almost every continent (except mainland Antarctica and a few islands, such as Greenland), and from the equator to past the arctic circles.

Ants are also relatively diverse, with over 15,000 described species, from over 400 genera, in 17 extant subfamilies (Bolton 1995). Along with being diverse, ants can also be abundant, living in large eusocial colonies, and utilizing up to 20-25% of terrestrial animal biomass (Shultz 2000). Being abundant, ants are easily sampled, with pitfall trapping or even hand collection being simple methods to record the presence of ant species (Bestelmeyer et al. 2000). These factors, in addition to their ecological

1 importance which will be expanded on in the next sections of this chapter, make ants a valuable focal taxon.

1.1.2 Ants and the environment

Species richness patterns across the Earth often follow a latitudinal diversity gradient, with more species at the equator and less towards the poles (Gaston 2000). Speciation, extinction rates, and energetics have all been used to help explain global diversity patterns (Dunn et al. 2009; 2010). For ants, several studies have shown that ant species richness is highest at the equator and lower towards the poles (Kaspari et al.

2004; Dunn et al. 2009). Factors associated with latitude, such as mean annual temperature, precipitation, and net primary productivity have been found to correlate to ant species richness at a global scale (Kaspari et al. 2004; Dunn et al. 2009; Dunn et al. 2010). The warmer, dryer, and more productive areas are all correlated with higher ant species richness and diversity (Dunn et al. 2010). However, global gradient patterns are still complex, and a comprehensive explanation of the latitudinal gradient pattern it is still not fully understood.

At more local levels, ants have been found to be affected by a wide range of environmental variables. Nesting locations, food availability, sunlight, inter- and intra- species competition can all play a role in modifying ant communities (Andersen 2000;

Kaspari 2000). Canopy structure is an important influencer in ant diversity. Thick canopy cover blocks out the sun and can reduce ant species richness within dense forests, especially in temperate areas (Punttila et al. 1996; Ivanov & Keiper 2010).

However, within tropical rainforests, tall, dense canopies, with diverse tree species can

2 be hotspots of arboreal ant diversity (Ribas et al. 2003). In northern temperate regions, coarse woody debris (i.e. fallen, rotting trees) is important as nesting sites for many ant species, and more wood is often correlated with more ant species (Higgins et al.

2017). Leaf litter is another important variable noted to be a major influencer of ant species richness, being an important refuge for ants, their food, and providing valuable nesting sites (Shik & Kaspari 2010). However, in open environments, open ground is important in providing thermal energy in more temperate regions (Radtke et al. 2014).

Soil type has also been found to play a major role in structuring ant communities, with sandy soil areas being richer in ant species than clay based soils (Boulton et al. 2005).

1.1.3 Ants and disturbance

Habitat disturbance is a common process that can have a range of positive and negative effects on an ecosystem depending on history and intensity. Use of ants to monitor changes in community structure from disturbances such as fire, deforestation, mining, urbanisation, grazing (natural and agricultural), agriculture, and flooding is common (Philpott et al. 2010). Many ant species are relatively resilient to less intense disturbances, such as fire or grazing which commonly result in changes to community composition instead of overall ant species richness (Hoffmann and Andersen 2003;

Philpott et al. 2010; Glasier et al. 2014). However, more intense disturbances, such as mining (Hoffman 2000), deforestation (Dunn et al. 2004), and urbanisation (Lessard &

Buddle 2005) are known to reduce ant species richness. These compositional changes in ant diversity from disturbance can be important in examining how ecosystems themselves change and how disturbances modify them.

3

Ants themselves can become disturbances in ecosystems. Introduced species can change environments, cause problems in agriculture, have negative interactions with humans (through stinging and biting), and can change invertebrate communities

(Suarez et al. 2010). Invasive ant species often have large colonies, can quickly exploit resources, and are able to dominate native ants, resulting in drastic changes in areas they have been introduced (Lach & Hooper-Bui 2010). In Australia, the introduced

Pheidole megacephala dramatically decreased macroinvertbrates and native ant diversity in sites it was found (Hoffman & Par 2008). In the United States, Linepithema humile is well known to disrupt native ant communities (Carointero et al. 2007), reduce insect diversity (Krushelnychy and Gillespie 2008), and forms mutualisms with

California red scale (Aonidiella aurantii) a pest of citrus trees, resulting in economic damage to fruit crops (Martinez-Ferrer et al. 2003). The changes that invasive ants have on ecosystems can be dramatic and can be long lasting.

1.1.4 Ant ecology

Along with their diversity and abundance, ants are dominant ecological entities. Soil modification is one major reasons ants are often labelled ecosystem engineers. The increase of nutrients from ant faeces, corpses, and food storage is often exploited by microbes and plants (Ohashi 2007). Moreover, ants play a major role in soil turnover

(and consequently nutrients) within the environments they inhabit (Folgrait 1998). The bioturbation from gallery excavation increases infiltration of water, for example in arid

Australia, galleries and nest entrances of Aphaenogaster ants significantly increase

4 water penetration into arid soils (Eldridge 1993). Ants further play a major role in the breakdown of wood, by excavating galleries and reducing it to smaller sizes more easily degraded by microbes and other organisms (Hansen & Klotz 2005). This importance to nutrient cycling and soil turnover often leads to ants being labelled keystone species that are integral parts of ecosystems.

Ants are also direct facilitators of biodiversity. They are the major dispersers of seeds from over 3000 plant species (Ness et al. 2010). Furthermore, ants play an important part of the food web, being major predators and/or influential herbivores (Hölldobler

& Wilson 1990). Formica ants are major predators of invertebrates in northern temperate climates (Domisch et al. 2009), while driver and army ant colonies from

Africa and South America, respectively, are often labelled apex predators feeding on invertebrates and vertebrates that are unable to escape their path (Hölldobler and

Wilson 1990). Ants can be just as important herbivores; for example, Atta leaf-cutter ants from South America can consume ~15% of leaf production per year within tropical savannas (Cherrett 1986). Contrastingly, ants are also important food sources for invertebrates, such as spiders, and vertebrates such as birds (Beckwith and Bull 1985;

Ellison et al. 2012). Being predators, prey, dispersers, and herbivores mean ants are integral to biodiversity.

Another way ants facilitate biodiversity, is through associations with other organisms.

Myrmecophiles, organisms that capitalize on the social fabric of ant societies (Parker

2016), are diverse and abundant, making up a wide array of organisms (Kistner 1982).

Ant-plant mutualisms exist across tropical and subtropical climates, with

5 myrmecophytic plants hosting ant colonies for mutual protection (Davison & McKey

1993). A vast array of invertebrates also associate with ants; from phoretic mites using ants as a mode of transport, to beetles stealing food from the mouths of their ant hosts, to ants farming aphids for their honey-dew excretions (Hölldobler & Wilson

1990). These symbiotic relationships are diverse, and range from beneficial mutualisms to antagonistic parasitisms. Ant mutualisms can be diverse; for example, some species of bees and ants utilize the same nest for combined defense (Sakagami et al. 1989), or ants may protect aphids or caterpillars from predators an in return they are provided honeydew (sugary exudates) (Kaminski et al., 2010; Tegelaar et al., 2012).

Commensalisms with ants can also be diverse, such as myrmecophilic crickets or isopods living within an ant colony, or organisms such as moth larva feeding on the refuse piles that ants produce (Sanchez-Pena et al., 2003; Komatsu et al. 2009).

Myrmecophiles with antagonistic relationships with their ant hosts are also abundant.

Kleptoparasitic Coleoptera and Lepidoptera have evolved to steal food through mimicking communicative chemicals (Akino 2002), audio cues (Sala et al., 2014), and/or tactile touch (Hölldobler 1971) to trick ants into feeding them. Many butterflies within the Family Lycaenidae, have evolved to infiltrate ant nests where they are fed by their hosts or even eat ant larvae (Sielezniew et al. 2009). Moreover, many beetles

(Parker 2016), parasitic wasps (Huggett & Masner 1983), and spiders (Porter 1985) have evolved to exploit the nutritious and often abundant larvae within. These myrmecophilic species are diverse, widespread, and show how important ants are for facilitating biodiversity.

6 1.2 Research Objectives

The main research objective of this thesis was to examine the ecological importance of how ants influence and are influenced by, different interactions, be it with myrmecophiles, the environment or disturbance. Using the background information presented on ants in the previous sections of this chapter (Sections 1.1.1-1.1.4), I constructed a simple conceptual model to visualize how the environment, disturbance, and myrmecophiles interact with ants and vice versa (Fig 1.1). In designing this model,

I kept it simple to show general patterns found in other research. For example, in section 1.1.2, both global (e.g., mean annual temperature (Dunn et al. 2009)) and local

(e.g. leaf litter cover (Shik & Kaspari 2010)) environmental variables were found to greatly influence ant species composition and richness, therefore the environmental pathway to ants is strong (Fig. 1.1). However, ants are also considered ecosystem engineers (Hölldobler & Wilson 1990), creating their own local environment, and indicating there should be a weak pathway from ants to the environment within the conceptual model (Fig. 1.1). Following this process, the model was constructed for each pathway, to help lay the groundwork for my thesis and provide a framework for my chapters. Additionally, being simple, the model allows a visual representation of how each pathway was tested within a chapter and the ability to compare chapters more easily.

7

Figure 1.1 Conceptual model showing effects of environment, disturbance, and myrmecophiles on ants. Black arrows represent conceptual strength of interactions. Numbers and dashed arrows represent the chapters of this thesis, and the interactions that are discussed within a chapter.

1.3 Thesis Structure

In Chapter 2, I model how the global environment and ant species richness influence myrmecophile species richness on a global scale (Fig. 1.1). Using a database of myrmecophiles compiled from 350 references, which includes locality information, their relationship with ants, and climatic variables, I ask “does global environment climate or host species richness play a larger role in the richness of myrmecophiles?”.

To do this I compared models including regional ant species richness (number of hosts species) and climatic variables such as annual temperature, precipitation and net primary productivity to see which variables most influence myrmecophile species

8 richness. Additionally, I model how different symbiotic relationships displayed by myrmecophiles (mutualisms, commensalisms, kleptoparasitisms, and parasitisms) are affected by these variables.

Chapter 3 models the interactions between ant traits and myrmecophiles (Fig. 1.1). In this chapter, I ask how ant traits such as colony size, eye size, presence of a sting, number of spines and taxonomic relation (subfamily) influence he number of myrmecophiles an ant species associates with. Furthermore, I look at how the previously stated ant traits influence the number of different myrmecophile relationships (mutualisms, commensalisms, kleptoparasitisms, and parasitisms) ants have, by modelling which traits influence myrmecophile associations. The global database of myrmecophiles from chapter two was also used, with ant traits added.

Chapter 4 once again uses the myrmecophile database, but specifically examines how the type of relationship between myrmecophiles and ants influences host range of myrmecophiles (Fig. 1.1). I examined and compared the average host range of major myrmecophile orders, such as Lepidoptera, Coleoptera, Hymenoptera, and Diptera.

Moreover, I modelled how host range changed along a gradient from beneficial to detrimental relationships that myrmecophile have with ants.

Chapter 5 focuses on how grazing history and intensity influences the local environment and ant communities (Fig. 1.1). This field work was done in arid woodlands of New South Wales and focused on comparing the effects of grazing on above- and below-ground ant communities. To conduct this research over 340,000

9 ants, comprising of 114 species, were sampled and analyzed. Localities were assessed as currently grazed, recently ungrazed (no grazing for at leas t three years), and long ungrazed (no grazing in the last 35 years). Sites sample at each locality were along a gradient from water, acting as a proxy for grazing intensity, as grazers cause a piosphere effect where areas closer to water are more frequently foraged. With sample data of ground cover, grazing history and intensity, I was able to model which variables most influenced above- and below-ground ant communities. This chapter is in review at Ecosystems.

Chapter 6 provides a synopsis of my results, critically discusses the ecological implications of the research and also explores future research directions.

10 Chapter 2

Climate or host richness: what drives global myrmecophile species richness?

2.1 Abstract

The latitudinal gradient in diversity is one of the most striking patterns in global biodiversity. Understanding what factors drive this gradient continues to be a major focus in ecology, with proposed mechanisms including relationships with climatic variables and the nature of species interactions. To examine the relative strength of climatic variables and ant host species richness on myrmecophile species richness

(organisms that capitalize on the social fabric of ant biology), we tested whether variation in temperature, precipitation, net primary productivity, and the number of host species could explain large-scale variation in the species richness of myrmecophiles. Additionally, we further tested if those same variables affected the richness of species representing differing symbiotic relationships (mutualisms, commensalisms, kleptoparasitisms, and parasitisms). Our findings indicate that the overall species richness of myrmecophiles increases toward the equator/ However, the predictors of species richness differed for different myrmecophile relationships, wi th ant species richness only predicting myrmecophile richness for commensal species, while climatic variables (annual temperature, temperature variation, precipitation, and net primary productivity) were more important for mutualists, kleptoparasites, and parasites. Our findings show that abiotic factors are important in the evolution and

11 richness of symbiotic relationships involving myrmecophiles, in addition to richness of hosts.

2.2 Introduction

The latitudinal diversity gradient is a striking pattern of global ecology (Rohde 1992;

Koleff & Gaston 2000; Mittelbach et al. 2001). For most marine, freshwater, and terrestrial ecosystems, there are more species in areas closer to the equator

(Hillebrand 2004). However, this diversity gradient is not homogenous or continuous, can vary at different spatial scales across the landscape, and some groups of organisms exhibit the opposite pattern increasing in richness towards the poles (Kindlmann, et al.

2007). A global explanation on what mechanisms drive these global patterns in species richness remains highly elusive (Gaston 2000; Willig et al. 2003; Mittelbach et al.

2007).

While species richness commonly covaries across latitudinal gradients, latitude is not a causal factor but a correlate of contemporary climate (Gasto, 2000; Allen et al. 2002).

Multiple abiotic mechanisms have been suggested to drive the latitudinal diversity gradient, often involving available energy and resources related to climate. Annual mean temperature, mean temperature variation, and precipitation are known to be postively related to species richness for many organisms such as amphibians (Allen et al. 2002), ants (Dunn et al. 2009), birds (Rabinovich & Rapoport 1975), mammals (Allen et al. 2002), and trees (Currie & Paquin 1987). Net primary productivity, which also

12 varies with latitude, commonly correlates with an increase in species richness in many vascular plants as well as some animals (Mittelbach et al. 2001; Gillman et al. 2015).

While abiotic factors are most often used to explain patterns in overall species richness, variation in species interactions has also been proposed as a mechanism that influences the richness of species. The intensity of predation, herbivory, and parasitism can vary along latitudinal gradients (Schemske et al. 2009; Moles 2013), with the potential to drive coevolution and rates of speciation. For organisms that rely on a host, be it plant or animal, host species richness is a likely determinant of large-scale patterns in the richness of symbionts (e.g. mutualists, commensals, parasites)

(Novotny et al. 2006; Kamiya et al. 2014). The species richness of host plants is positively correlated with the species richness of many herbivorous insects (Janz et al.,

2006; Futuyma & Agrawal 2009). Species involved in mutualisms are frequently more species rich when more host species are available. For example, the species richness of symbiotic dinoflagellates is higher with more host coral species (LaJeunesse et al.

2004), fig wasp (Agaonidae) richness increases with increases in species richness of fig trees (Ficus) (Machado et al. 2005), and mycorrhizal fungi and plant species richness are positively correlated (Hiiesalu et al. 2014). The species richness of parasites is also frequently linked to host richness (Kamiya et al. 2014), as seen, in insect parasitoids

(Tylianakis et al. 2006), bird trematodes (Hechinger & Lafferty 2005), and fleas

(Krasnov et al. 2004). For all of these groups of symbionts, the processes causing large- scale patterns in species richness are thus likely to be a combination of the richness of their hosts and relationships with climatic variables.

13 Previous research with symbionts has shown varying patterns of species richness with latitude depending on their taxonomic group and/or relationship with their host(s).

Many herbivores exhibit the common pattern of high species richness at low latitudes

(e.g., butterflies (Janz et al. 2006)). Taxa such as Aphidae (aphids: Dixon et al., 1987) and Symphyta (sawflies: Kouki et al. 1994) exhibit patterns that are opposite, or trend in a humped-shaped distribution away from the equator. These exceptions have been explained by greater host availability and host range in temperate environments

(Kindlmann et al. 2007). Mutualists are often richest in low latitudes, for example, ant- plant mutualisms (Davidson & McKey 1993), coral symbiosis with zooxanthelle algae

(Connell 1978), and plant pollinators (Regal 1982).

Kleptoparasites are reliant on a host for food. Wcislo (1987) reviewed global species richness patterns of kleptoparasites and found that many hymenopteran (bees, wasps and ants) social parasites were richer in temperate than tropical regions, and proposed seasonality and the synchronisation of lifecycles for symbiont and host as an explanatory factor. Areas with high seasonal variation have a more predictable host abundance and availability, which is easier to exploit by a symbiont (Wcislo, 1987). For kleptoparasitic birds, high concentrations of host, high prey availability, food predictability, and food storage all play important roles in kleptoparasitism

(Brockmann & Barnard, 1979). Therefore, climates that promote reliable resources and host availability are integral for kleptoparasite diversity.

Parasites have conflicting richness patterns with many groups richest at low latitudes

(e.g., parasites of primates (Nunn et al. 2005), fish (Rohde 1999), and humans

14 (Guernier et al. 2004)). In other cases, parasite richness does not vary with latitude or are richer at higher latitudes (e.g., parasites of large mammalian carnivores (Lindenfors et al. 2007), ichneumonid wasps (Wcislo 1987), and some parasitic trematodes

(Torchin et al. 2015)). Explanations for the frequently observed higher richness of parasites at lower latitudes include milder climates (Harvell et al. 2002) and a greater availability (both in abundance and species richness) of host species (Poulin & Morand

2000). Increased body size of hosts has been proposed to explain the higher richness of groups more diverse at higher latitudes (Lindenfors et al. 2007).

We use data compiled from a global synthesis of myrmecophiles to quantify large scale patterns in the richness of an abundant group of symbiotic organisms and test the relative importance of abiotic variables and host richness in explaining these global patterns. Myrmecophiles are symbiont organisms “that capitalize on the social fabric of ant biology” (Parker 2016). Ants are globally ubiquitous, and their species richness has been shown to exhibit the common latitudinal gradient of reduced species richness with distance from the equator (Dunn et al. 2009). Like their ant hosts, myrmecophiles are also globally distributed, making them ideal group to test how species interactions change over latitudinal and climatic gradients.

From a global data set of 1605 species, we aimed to test if the species richness of myrmecophiles follows a latitudinal gradient, and is best explained by host availability

(ant species richness), or the important abiotic variables of temperature, temperature variation, precipitation and net primary productivity. The type of relationships that myrmecophiles have with their ant hosts, from beneficial (mutualistic), neutral

15 (commensal) to detrimental (kleptoparasitic to parasitic), was quantified to test how relationship type affects global patterns of species richness. We predicted that (1) ant species richness would be an important correlate of overall myrmecophile richness, as host availability has been cited as a major factor in symbiont species richness; (2) mutualist richness would be greatest at low latitudes (least influenced by abiotic effects) as the benefits of facilitation would be expected to be greater under harsher conditions, thus reducing environmental stress on species richness; (3) neutral relationships (commensals) would be richest in low latitudes and areas of high ant species richness, as this relationship would arise more when there are more ant species available, and (4) antagonistic symbionts (kleptoparasites and parasites) would be most diverse at higher latitudes, and influenced by abiotic factors, as previous studies have shown that climate and seasonality may be a driving force in the richness of social parasites (Wcislo 1987).

2.3 Methods

2.3.1 Data collection

To create the global data set, we searched for publications indexed in the ISI Web of

Science using the terms: “myrmecophil*” or "ant associat*" or "ant inquiline" or

"synechtran*" or "synoekete*" or "symphile*" or "trophobiont*". These searched words are all associated with myrmecophiles and their relationships with ants

(Hölldobler & Wilson 1990). With problems of identification in references and the need to exclude certain taxonomic groups for our research, we felt it necessary to provide a working definition of myrmecophile. The word ‘myrmecophile’ is derived from the

16 Greek ‘myrmex’ (ant) and ‘philos’ (loving), so in simple terms, myrmecophile means

“ant-lover” (Kronauer & Pierce 2011). Other definitions that are frequently cited are

“an organism found in association with ants” (Kistner 1982) and “any organism that is dependent on ants at least during part of its lifecycle” (Hölldobler & Wilson 1990). To test our hypotheses, however, we followed Parker’s (2016) definition of myrmecophiles as “species that capitalize on the social fabric of ant biology”.

Of a total of 787 results, we selected those involving only invertebrate myrmecophiles, excluding fungi, microbes, and plants. Mites (Subclass: Acari), nematodes (Phylum:

Nematoda), and Collembola (Subclass: Collembola) were also excluded from the study as while many species of these three invertebrate groups have been reported from ant nests, and may be true myrmecophiles (Rettenmeyer et al. 2011), many published studies do not allow us to conclusively determine their relationship with ants (Parker

2016). Additionally, both mites and Collembola were rarely identified to species in the available literature as stated in Campbell et al. (2013).

2.3.2 Definitions

Publications from our literature search were only included in our analysis if: (1) organisms fit our definition of a myrmecophile, (2) the myrmecophile was identified to species or species group; (3) host ant was identified to species or species group, (4) a specific collection locality was given, and (5) the relationship a myrmecophile had with its host was described. Further studies were added by examining the reference lists from each paper found. Under these search criteria, we compiled a data set derived

17 from 350 published studies (Appendix S1). Additionally, we made the effort to correct for nomenclature synonyms for both ants and myrmecophiles to the best of our ability.

The relationship types of myrmecophiles were classified into four types ranging from positive to negative associations: mutualist, commensal, kleptoparasite, or parasite.

Mutualists were defined as having an association that benefited both myrmecophile and ant host (for example, aphids farmed/protected by ants (Stadler & Dixon 2008), or bees co-habiting with ants in a nest for mutual protection (Sakagami et al. 1989)).

Commensal relationships were defined as associations where myrmecophiles benefited, but there were no benefits or detriments to the ant host (for example, moth larva living in middens of an ant colony (Sanchez-Pena et al. 2003) or crickets living within a colony, but not using ant resources (Komatsu et al. 2009)). For this study, kleptoparasites were associations where myrmecophiles stole food and/or resources from their ant hosts, but did not prey upon them (for example, beetles that steal food from passing ants or are fed by ants (Lencina et al. 2011; von Beeren et al.

2011)). Parasites were defined as myrmecophiles that harmed their hosts, by feeding directly on ants and/or their brood. Organisms that steal food and predate on ants, such as some lycaenid butterfly larva (Thomas & Elmes 2004; Witek et al. 2008) were also classified as parasites. Associations were cross checked among different references and the most supported association used.

18 2.3.3 Global richness

To obtain data on species richness of myrmecophiles at a global scale, we first used the software Biodiverse (Laffan et al. 2010) to divide the world into 2° by 2° grids. ArcGIS was then used to map the sites of each myrmecophile record into relevant grids (ESRI

2011). The species richness and number of unique sites “sampled” (reported from the literature) within each grid were then calculated.

2.3.4 Statistical analysis

To test the hypothesis that myrmecophile relationships and species richness are explained by climatic variables, we chose predictor variables that have been shown to be correlated with species richness and biodiversity in many studies. Annual temperature variation, and annual precipitation have all been shown to be correlated with ant species richness (Kaspari et al. 2000; Dunn et al. 2009), as well as global species richness (Hawkins et al. 2003). Net primary productivity has also been shown to be correlated with high global species richness (Costanza et al. 2007). Mean annual temperature and temperature variation (measured in °C) and annual precipitation

(measured in mm) were obtained from the Worldclim database (Hijmans et al. 2005).

Mean annual temperature variation was the measure of the lowest monthly average subtracted from the highest monthly average. Net primary productivity was measured in units of elemental carbon, and was obtained from ArcGISData (Imhoff et al. 2004).

Data were at a resolution of at least 5 arc minutes (Hijmans et al. 2005). Using ArcGIS, variables were extracted for each record and then averaged for each grid.

19 In addition to climatic variables, we considered ant species richness in each of the grid cells as the number of potential hosts. Data for ant species richness were obtained from the country and region species richness database from AntWiki.org (AntWiki

2015). The best regional scale data for the 2° by 2° grids were used.

All predictor variables were standardized using the following formula: y = ((xi – (max(x)+min(x))/2))/((max(x)-min(x))/2) where y is the standardised variable, xi is the measured variable. This standardization transformed the data between -1 and 1 (Kleijnen 1997) and allowed us to directly compare the effects of variables. Generalized linear models with a negative binomial distribution were used to test if latitude influenced myrmecophile species richness in the R package ‘MASS’ (Venables, & Ripley 2002). To test which variables (climatic and host species richness) best predict myrmecophile species richness, we used negative binomial glm models and contrasted models with all combinations of predictor variables using the function dredge from the R package ‘MuMIn’ (Barton 2015).

Models were first ranked using Akaike’s Information Criteria (AIC; Burnham &

Anderson 2011), and then ranked by Akaike weights (wi), which determines the likelihood a model is the best model (Wagenmakers & Farrel 2014). Additionally, only models within the standard confidence set from the best fit model (ΔAIC < 2) were used to derive model average coefficients, standard errors, and relative variable importance (RVI; Barton 2015); models with ΔAIC > 2 were excluded in those calculations as they are considered statistically different from the first model

(Burnham & Anderson 2011). Best fit models were visualized with the R package

20 ‘visreg’ (Breheny & Burchett 2013). Relative variable importance (RVI) was then used to determine which variables were most influential on species richness.

The number of unique sites within each 2° by 2° grid was used to account for variation in sampling effort among geographic regions. A total of 752 unique sites were recorded from the literature. Using linear regression, the number of sites within a grid was shown to be a significant predictor of myrmecophile species richness with the more sites sampled, the higher species richness using linear regression (P < 0.001, df =

539; Fig. 2.1a). To account for this sampling bias, we used the number of sites sampled within each grid as a statistical offset in each model, instead of a covariate. A statistical offset controls for sample bias, reduces the influence that the number of sites sampled has on our myrmecophile species richness, and helps to better model the effects of other variables (Werner & Guven 2007).

2.4 Results

2.4.1 General results

Our literature synthesis identified 1605 myrmecophile species from 127 families and

20 orders of invertebrates, derived from 4399 records in 350 publications (Table 2.1).

Species from the Coleoptera comprised ~64% of reported species associated with ants

(Table 2.1). Other speciose orders with 50 or more species of myrmecophiles were the

Diptera, Hemiptera, Hymenoptera and Lepidoptera (Table 2.1). Kleptoparasitic relationships were most commonly reported (36% of species), while parasitic relationships were reported the least (12.5%, Table 2.1). A total of 540, 2° by 2° grids,

21 were sampled with a range of 1 to 155 myrmecophile species found within a grid.

Sampled grids were on all continents except Antarctica (Fig. 2.1).

22 Table 2.1 The orders of invertebrates that are known myrmecophiles, with the number of species and families of myrmecophiles per order, and the number of species for each type of relationship the myrmecophile has with ants. Relationship type Order Species Families Mutualist Commensal Kleptoparasite Parasite Coleoptera 1028 35 2 396 538 92 Hemiptera 289 25 282 0 0 7 Lepidoptera 70 5 39 4 17 10 Diptera 57 6 0 4 5 48 Hymenoptera 51 16 5 3 1 42 Isopoda 23 8 0 23 0 0 Orthoptera 16 2 0 6 10 0 Polydesmida 14 4 0 14 0 0 Araneae 9 7 1 6 0 2 Blattodea 9 4 0 6 3 0 Geophilomorpha 9 3 0 9 0 0 Thysanura 9 3 0 5 4 0 Lithobiomorpha 6 1 0 6 0 0 Julida 4 1 0 4 0 0 Pseudoscorpionida 4 2 0 4 0 0 Isoptera 3 1 0 3 0 0 Dermaptera 1 1 0 1 0 0 Neuroptera 1 1 0 1 0 0 Polyxenida 1 1 0 1 0 0 Thysanoptera 1 1 0 1 0 0 Total 20 1605 127 331 497 578 201

23

Figure 2.1 Modelled relationships between global myrmecophile species richness and highly influential variables. a) number of sites, b) absolute latitude (i.e., degrees from the equator), c) ant species richness, d) mean annual temperature, e) temperature variation, f) annual precipitation and g) net primary productivity. Variables c) to g) were all found to be in the best model to explain global myrmecophile species richness. Lines are calculated using the ‘visreg’ function in R (Breheny & Burchett 2013), with 95% confidence intervals. Models b) to g) are corrected for number of sites sampled within a 2° grid.

24

Table 2.2 Comparison of best-performing models effecting myrmecophile and relationship-type species richness. Each row contains the intercept and parameter coefficients that comprised a single model, along with the number of parameters (K), corrected Akaike’s Information Criteria (AICc); change in AIC from best model (ΔAIC); Akaike Weights (wi). Best ranked model for each group is bolded.

Mean annual Ant species Mean annual Mean annual Net primary Intercept temperature K AICc ΔAIC w richness temperature precipitation productivity i variation Myrmecophiles 2.06 0.29 -0.52 -0.62 -0.81 0.74 7 2732.26 0 0.86 Mutualist 2.00 -0.71 0.99 1.10 5 1261.94 0 0.17 1.73 0.31 -0.78 1.75 5 1261.98 0.04 0.17 2.08 0.27 -1.00 -0.13 0.90 1.15 6 1262.11 0.17 0.16 1.55 -0.54 1.70 4 1262.33 0.39 0.14 1.96 -0.84 -0.17 0.54 1.03 6 1263.87 1.93 0.07 2.18 -0.73 1.92 4 1263.91 1.97 0.06 Commensal -0.30 0.64 -0.93 -1.23 5 1255.90 0 0.25 -0.35 0.62 -0.86 -1.73 0.63 6 1256.59 0.69 0.18 -0.41 0.63 0.35 -0.73 -1.35 6 1257.25 1.35 0.13 -0.25 0.74 0.78 -1.96 0.92 6 1257.39 1.49 0.12 -0.50 0.60 0.44 -0.60 -1.96 0.73 7 1257.53 1.63 0.11 Kleptoparasite 0.23 -1.11 -1.35 0.83 5 1740.55 0 0.27 0.31 0.16 -0.99 -1.35 0.81 6 1741.06 0.51 0.21 0.24 -0.32 -1.37 -1.33 0.82 6 1741.52 0.96 0.17 0.32 0.16 -0.33 -1.26 1.33 0.81 7 1741.92 1.36 0.14 Parasite 0.40 -0.71 0.54 -0.69 5 1221.54 0 0.27 0.92 -0.75 0.64 4 1222.55 1.01 0.16 0.22 -1.10 -0.83 4 1223.25 1.71 0.11 0.38 -0.70 0.57 -0.84 0.18 6 1223.33 1.79 0.11 0.42 0.03 -0.73 0.56 -0.69 6 1223.54 2.00 0.10 25

Figure 2.2 Global myrmecophile species richness in 2° by 2° grids. Larger and lighter coloured circles represent higher species richness . Each point represents the middle of the 2° by 2° grids.

26 2.4.2 Overall myrmecophile richness

The species richness of all myrmecophiles increased with decreasing distance from the

equator (P = 0.027, df = 538; Fig. 2.1b). The most strongly supported predictive model

of myrmecophile species richness included all variables (wi = 0.86; Table 2.2). Relative

variable importance (RVI) found that all variables were equally influential in the

predictor model (Fig. 2.4a). Ant species richness and net primary productivity were

positively correlated with myrmecophile species richness, while mean annual

temperature, mean annual temperature variation and mean annual precipitation were

negatively correlated with myrmecophile species richness (Fig. 2.1 & Fig. 2.4a; Table

2.2).

2.4.3 Mutualist species richness

The richness of mutualist species did not vary with latitude (P = 0.87, df = 538; Fig.

2.3a). No model explaining mutualist species richness was strongly supported, with the

top two models having the same Akaike weightings (wi = 0.17, Table 2.2). Relative

variable importance (RVI) values indicated that mean annual temperature and net

primary productivity were the most influential predictors of mutualist species richness

(Fig. 4b). Model average coefficients indicated that mean annual temperature was

negatively, and net primary productivity positively, related to mutualist species

richness (Fig. 2.4b).

27

Figure 2.3 Variation in global species richness per 2° grid of myrmecophile relationships with absolute latitude (i.e., degrees from the equator). Lines represent fit models using the visreg function in R (Breheny and Burchett 2013), with 95% confidence intervals. Models are absolute latitude corrected for number of sites sampled at that latitude. (*) indicates a significant effect (P< 0.05) of latitude on myrmecophile species richness.

28

Figure 2.4 Model average coefficients and Relative Variable Importance (RVI) of predictor variables for species richness of all myrmecophiles and myrmecophile relationship-types. Error bars represent 95% confidence intervals. Variables are listed according to rank by RVI for each modelled group.

29 2.4.4 Commensal species richness

Increasing latitude was negatively correlated with commensal species richness (P <

0.001, df = 538; Fig. 2.3b). The strongest model explaining commensal species richness

included ant species richness, mean annual temperature variation and mean annual

precipitation (wi = 0.25, Table 2.2). However, several other models had close Akaike

weights, with the second strongest model including net primary productivity (wi = 0.18,

Table 2.2). Relative variable importance (RVI) values indicated that ant species

richness, mean annual precipitation, and mean annual temperature variation were the

strongest predictors of commensal species richness (Fig. 2.4c). Model average

coefficients showed that commensal species richness was positively correlated with

ant species richness, but mean annual temperature variation and mean annual

precipitation were negatively correlated (Fig. 2.4c).

2.4.5 Kleptoparasite species richness

Increasing latitude was negatively correlated with kleptoparasite species richness (P

<0.001; df = 548; Fig. 2.3d). The model: mean annual temperature, mean annual

precipitation, and net primary productivity was the strongest in explaining

kleptoparasite species richness (wi = 0.27, Table 2.2). However, the second ranked

model (wi = 0.21, Table 2.2) also included ant species richness. Variables with the

highest RVI were mean annual temperature variation, mean annual precipitation and

net primary productivity (Fig. 2.4d). Mean annual temperature variation and mean

annual precipitation both had negative correlations, while net primary productivity

had a positive correlation with kleptoparasite species richness (Fig. 2.4d).

30 2.4.6 Parasite species richness

Parasite species richness increased with distance from the equator (P < 0.001; Fig. 2.3).

The most strongly supported model explaining parasite species richness was mean

annual temperature, mean annual temperature variation, and mean annual

precipitation (wi = 0.27, Table 2.2), followed by the model mean annual temperature,

mean annual temperature variation (wi = 0.16, Table 2.2). Mean annual temperature,

mean annual temperature variation, and mean annual precipitation were also ranked

highest in RVI (Fig. 2.4e), further supporting them as the main drivers of parasite

species richness. Mean annual temperature and mean annual precipitation were

negatively correlated with parasite species richness, while mean annual temperature

variation displayed a positive relationship (Fig. 2.4e).

2.5 Discussion

2.5.1 Overall myrmecophile richness

Our global analysis indicated that the species richness of myrmecophiles was highest at

lower latitudes. However, this pattern was not consistent for all types of relationships.

The richness of mutualist species did not vary with latitude, and parasites were more

species-rich at higher latitudes. Furthermore, species richness of myrmecophiles was

not simply a function of richness of available ant hosts, but was also related to

differences in climatic variables. Additionally, relationships among climatic variables

and myrmecophile species richness varied among the different types of relationships,

implying that climate may be an important correlate in determining richness of

symbiont relationships.

31

Species richness of myrmecophile relationships was more often correlated with climatic variables than ant host-species richness. Many studies have focused on host availability (such as species richness) when examining species richness of symbionts

(Kamiya et al., 2014), but our study showed that most relationship types (mutualist, kleptoparasites, and parasites) were correlated with climatic variables rather than species richness. These findings indicate that climate may play a more important role in driving the evolution of symbiont associations than has is previously thought.

2.5.2 The richness of mutualist myrmecophiles shows no latitudinal gradient

The only group of myrmecophiles showing no pattern of species richness with latitude was the mutualists and our model selection approach did not detect a single set of predictor variables likely to explain the richness of mutualist myrmecophiles. This contrasts with previous reports of patterns in richness for other mutualisms. For example, ant-plant mutualisms, where ants protect specialized plants that they live within, are restricted to the tropics (Davidson & McKey 1993), and coral symbionts also have higher species richness in tropical compared to temperate waters (Huang et al.

2011). In contrast, nitrogen fixing mutualisms between plants and actinomycetes tend to be higher in temperate areas than the tropics (Boucher et al. 1982). Although latitude did not explain mutualist richness, other variables were shown to be important. Mean annual temperature and net primary productivity were the best predictors of mutualist species richness (Fig. 2.4b). Most mutualist myrmecophiles in our study were from the order Hemiptera, and of the Hemiptera, families such as

Aphidae in the suborder Sternorrhyncha, or Membracidae in the suborder 32 Auchenorrhyncha have noted high species richness in temperate climates (Wood &

Olmstead 1984; Hullé et al. 2010). Higher species richness of these groups in temperate regions may be due to host plant availability (Heie 1994). Although plant species richness is lower in temperate areas, the chances of finding a suitable host may be easier because individual species are more widespread (Dixon et al. 1987; Heie

1994).

The positive influence of net primary productivity on mutualist species richness is likely driven by the type of relationship between symbiont and host. Most myrmecophile mutualisms are based on a symbiont providing food to ants in return for protection

(Hölldobler & Wilson 1990). Because the food provided is “honey-dew”, the excess sugar from consuming plant sap, plants play an important role in this ant- myrmecophile mutualism. Areas with higher net primary productivity would therefore coincide with a greater abundance of resources for herbivores, leading in turn to a greater probability of forming mutualisms between ants and herbivores.

2.5.3 Commensals and the importance of ant apecies richness

Like many organisms, we found that the species richness of commensal myrmecophiles was highest at low latitudes (Fig. 2.3). Moreover, commensals were the only relationship type where the ant species richness was an influential predictor

33 of their richness. As commensals utilize “neutral” resources of ants, such as security, exploiting ant colony waste, or using the engineered environment of a colony as a place to live (Hölldobler & Wilson 1990; Sanchez-Pena et al. 2003; Komatsu et al.

2013), the more ant species, the greater the chance of establishing interactions. As host species richness has been attributed to other non-myrmecophile symbionts species richness (Pӓivinen et al. 2003; Krasnov et al. 2004; Hechinger & Lafferty 2005), it is surprising that commensals were the only group to show this trend.

Climate was also a predictor of commensal myrmecophile species richness. High precipitation and high temperature variation were negatively correlated with commensal species richness (Fig. 2.4) and these factors are harder to explain. Recent work has suggested that more stable ecological systems are driven by commensalisms

(Mougi 2016). This may suggest that areas with a constant/ stable climate may also favor commensal relationships over antagonistic or beneficial ones. When climatic variables become more extreme (higher temperature variation and high precipitation), commensalisms may no longer be beneficial and more antagonistic symbiont relationships may benefit.

2.5.4 Kleptoparasites: climate and resource stability

Kleptoparasites had higher species richness at lower latitudes, which is contrary to previous studies of invertebrate kleptoparasitism. Hymenopteran kleptoparasites, including kleptoparasitic ant species (ants that enslave or steal food from other ants)

34 (Hölldobler & Wilson 1990; Buschinger 2009), are more diverse in temperate than tropical areas (Wcislo 1987). The opposite species richness patterns found between kleptoparasitic myrmecophiles and kleptoparasitic ants is an intriguing contrast that requires more study to understand.

The most influential variables in predicting the species richnes s of kleptoparasites were all abiotic (mean annual temperature variation, mean annual precipitation, and net primary productivity). Combining all three variables indicates that drier areas with a lower variation in annual temperature and with greater productivity (net primary productivity) support greater kleptoparasite richness. This is consistent with theoretical predictions that kleptoparasites require higher availability, reliability, and stability of food resources from a host (Iyengar 2008).

2.5.5 Parasites: seasonality and the need of reliable hosts

Parasitic myrmecophiles were more species rich at higher latitudes. This is similar to the large-scale pattern in richness of many other parasitic relationships, such as parasites of mammalian carnivores (Lindenfors et al. 2007), parasitic bees and parasitoid wasps in Ichneumonidae (Wcislo 1987). However, species richness of parasites for primates (Nunn et al. 2005), humans (Gaston 2000), ectoparasites of fish

(Poulin 1992), and parasites of lizards (Salkeld et al. 2008) exhibit the more common trend of higher species richness towards the equator. These differences in patterns of species richness among parasitic organisms are not easily explained. However, host

35 species richness, body size, and host distribution have also been cited as factors in parasite richness (Wcislo 1987; Lindenfors et al. 2007).

As higher mean annual temperature and mean annual precipitation were negatively correlated with species richness, and mean annual temperature variation was positively correlated, the richness of parasitic myrmecophiles may be influenced by seasonality. Previous studies have suggested that seasonality enables parasites to exploit their hosts at reliable times of the year (Wcislo 1987). Ants offer a wide range of benefits to parasites in more temperate regions, such as high food availability/ reliability in summer months in the form of larval and homeostatic environments to inhabit for both summer and winter weather (Hölldobler & Wilson, 1990). Ant social parasites (ants that socially parasitize other ants) are more diverse in temperate areas

(Buschinger 2009), suggesting that higher latitudes drive more parasitic behaviours towards ants. However, our seasonality theory needs more testing. The finding that number of potential ant hosts was not a significant factor in determining parasite species richness is surprising, and may indicate that other host variables, such as colony size or ant body size, should be explored in the future.

Our results show that myrmecophile species richness overall followed global patterns in ant species richness (Dunn et al., 2009), but that these patterns varied among the types of relationship that myrmecophiles have with their ant hosts (mutualist, commensal, kleptoparasite and parasite). The relative importance of host richness and abiotic variables varied among relationship types with abiotic factors important in explaining the species richness of symbiont relationships. The importance of these

36 factors is related to resource availability, stability, and the life history traits (for example: sap feeding, breeding cycles) needed to maintain the symbiotic relationships exhibited by myrmecophiles.

We draw attention to two caveats of this study. First, although we recorded myrmecophiles from every continent, the data were not distributed evenly across the globe. Studies from Europe, North America, and Japan were well represented, but areas such as Central and Northern Asia, the Middle East, and Africa were underrepresented in our dataset. Although we attempted to account for different sampling intensities and therefore potential bias in richness of myrmecophiles and their ant hosts using number of sites sampled with each 2° by 2° grid “statistical offset”, this potential sampling bias cannot be ignored. Our results, however, represent the most comprehensive assessment of global myrmecophiles and their hosts to date, but as new data become available, the strength of our predictors could change. Second, our data were derived from multiple sources, methods, and time frames, as with any synthetic database. Despite this, we found clear trends in relation to abiotic factors, richness of ant hosts, and distance from the equator.

2.5.6 Conclusion

Our results show that myrmecophile species richness overall followed global patterns in ant species richness (Dunn et al. 2009), but that these patterns varied among the types of relationships that myrmecophiles have with their ant hosts (mutualist, commensal, kleptoparasite and parasite). The relative importance of host richness and abiotic variables varied among relationship types with abiotic factors important in 37 explaining the species richness of symbiont relationships. The importance of these factors is related to resource availability, stability, and the life history traits (for example: sap feeding, breeding cycles) needed to maintain the symbiotic relationships exhibited by myrmecophiles.

Publication details: Glasier James R.N., Poore Alistair G.B., Eldridge David J. (in review). Climate or host richness: what drives global myrmecophile species richness? Journal of Biogeography.

38 Chapter 3

Ant traits determine richness of myrmecophiles associated with individual ant species

3.1 Abstract

The study of symbiotic associations is an important topic in ecology, as associated species can have profound effects on one another. Determining symbiotic relationships, and how host traits affect the richness of symbionts is integral to our understanding of what drives these relationships, and how they influence biodiversity and species richness. To examine how host traits, affect symbiont species richness, we tested a set of ant host traits (subfamily, colony size, number of spines, presence of a sting, eye size) that are expected to influence the richness of myrmecophiles

(organisms associated with ants). Additionally, we tested how ant traits influence richness of symbiotic relationships exhibited by myrmecophiles (mutualisms, commensalism, kleptoparasitisms and parasitisms). Our findings indicate that colony size and number of spines are major drivers of myrmecophile species richness, with larger colonies, and more spines increasing richness. Moreover, these patterns were the same for myrmecophile relationships, though subfamily was also influential in determining richness of commensals and kleptoparasites.

39 3.2 Introduction

Symbioses are an important part of ecology as they can dramatically influence the population, fecundity and survival of both host and symbiont (Fritz 1982; Gulland

1992). These symbiotic relationships can range from highly specialised (one symbiont per host) to generalized (many per host). There is a long history of seeking to understand what controls the degree of specialisation, and what drives richness of symbionts associated with a host (Ezenwa et al. 2006). Suggested influences of symbiont richness are climate (Nunn et al. 2004), biogeography (Stat et al. 2006), shared evolutionary history (Ezenwa et al. 2006), and host traits such as size or defense traits (Päivinen et al. 2003). However, understanding how hos t traits affect the number of symbiont species per host is still not well understood.

In this study, we tested how ant traits determine the richness of myrmecophiles for

622 ant species. Ants are a ubiquitous group of social insects that are well studied, have a diverse set of morphological traits, diets, and colony sizes (Hölldobler & Wilson

1990; Lach et al. 2010). Found across most terrestrial ecosystems, ants can be considered ecosystem engineers as they move substantial volumes of soil, are important predators or herbivores, play a major role in nutrient cycling, and are an important food source for a wide range of organisms (Hölldobler & Wilson 1990:

Benoit 2013). As ants are well studied and ecologically important, we used ants as a focal taxon, documenting a large set of host traits from individual ant species to compare them with myrmecophile richness. Myrmecophiles are organisms (symbionts) that are dependent on ants for a part of their lifecycle (Hölldobler & Wilson 1990).

40 They represent a diverse group of taxa, and exhibit a wide range of symbiotic relationships (mutualisms, commensalisms, kleptoparasitisms and parasitisms) with their ant hosts (Kistner 1982). Like ants, myrmecophiles are well documented, allowing us to assemble an extensive dataset of 1629 myrmecophiles to compare how ant traits affect richness per ant species.

Evolutionary history can play an important part in determining symbiotic relationships.

Rapidly evolving host lineages are believed to easily gather symbionts from closely related species, along with coevolved species, increasing overall symbiont richness per host (Zietara & Lumme 2002; Nunn et al. 2004). Species-poor lineages, however, are suggested to have fewer symbionts because of more limited cross-transfer among species, but also through the loss of parasites when lineages have greater extinction rates (Nunn et al. 2004). Closely-related host species often share symbionts, or have closely related symbionts, and this can greatly affect symbiont richness (Poulin 1997;

Eastwood et al. 2006; Poulin et al. 2011). In primates, diverse lineages harbor a greater number of parasites per host species than species-poor lineages (Nunn et al. 2004). In myrmecophiles, cross species transfer, and multiple use of closely related hosts species, have been observed in several taxa such as the butterfly genus Phengaris

(Lycaenidae), where specialized parasite species will use closely related Myrmica ant species (Sielezniew & Stankiewicz 2008; Witek et al. 2010). Conversely, not all cross - species transfers of myrmecophiles involve closely related host species, particularly when it comes to mutualist myrmecophiles. Many taxa, such as aphids (Novgorodova

2005) or Parrhasius butterflies (Kaminski et al. 2012), may associate with multiple species from several different ant subfamilies, indicating that related hosts are not

41 always needed. For ant subfamilies, we would predict that the more species -rich subfamilies of ants, such as Myrmicinae and Formicinae (Bolton 1995; Antwiki 2017), would have more myrmecophile associations per species than species-poor subfamilies.

Body size or body mass, has been shown to be an important driver in many symbiotic relationships. Akin to island biogeography theory, larger-bodied hosts present larger patches of habitat, and are therefore able to support more species (Price 1980;

Ezenwa et al. 2006). In other organisms, such as hooved animals (Ezenwa et al. 2006), carnivores (Lindenfors et al. 2007), birds (Gregory et al. 1991) and primates (Nunn et al. 2007), larger body size is related to increased parasite richness. As ants are often labelled superorganisms (Hölldobler & Wilson 1990), where the colony, not the individual is the “organism,”, colony size is potentially a better measure than ant worker size. Larger ant colonies are easier for myrmecophiles to find and provide more available resources (in the form of food or defence) (Päivinen et al. 2003). Body size may also be important, larger ant sizes may allow for easier interactions and more resources, however, ant body size can greatly range within a species, making average body size a difficult measurement to attain compared to colony size. For other relationship types, such as mutualisms or commensalisms, there is limited research on the influences of body size on the number of symbionts. However, coral mutualisms do not follow the body size trend, and most often only a single species of mutualistic algae is associated with a host coral, irrespective of body size (Cook 1985). For ants, several studies have reported that colony size does influence myrmecophile species richness, specifically for myrmecophilic beetles (Hölldobler & Wilson 1990; Päivinen et

42 al. 2003). As larger colonies equate to more ants to provide better defenses, more resources, and are easier to find for myrmecophiles, we predict, as previous studies have found, that ant species with larger ant colonies will have more myrmecophiles.

Morphological traits are important in reducing predation, offering protection while hunting, or during intraspecies competition, and driving evolution in many taxa (Hunt

1983; Dornhaus & Powell 2010; Blanchard & Moreau 2016). These traits may also play an important role in the number of associations an organism is able to maintain. Ant traits, such as spines, stings, and eye size may influence their myrmecophile richness.

More Spines, functional sting, and large eyes have all been shown to reduce predation of ants (Blanchard & Moreau 2016), and may assist ants in interactions with other invertebrates. Ants with certain traits (for example more spines, the presence of a sting) may be able to reduce detrimental associations, or use their traits to protect beneficial associations (large eye size may be able to help protect mutualist myrmecophiles by detecting predatory threats).

Ants are morphologically and ecologically diverse, ranging from herbivores, to omnivores and predators, depending on the species (Hölldobler & Wilson 1990;

Blanchard & Moreau 2016). Ant diets may influence myrmecophile richness, as different symbiotic relationships (mutualists, commensals, kleptoparasites, and parasites) may exploit ant species that provide different resources. Herbivorous ants collect plant leaves or seeds, often storing food within nests and create waste piles from spoiled food (Cherrett 1986; MacMahon et al. 2000). These stored/excess resources provide an easier source of resources to commensal or kleptoparasitic

43 myrmecophiles than to mutualistic or parasitic species. Omnivorous ants, however, are more opportunistic, eat both plant materials and prey, and commonly form mutualisms with hemipterans (such as aphids), providing protection in return for honey-dew (excess sugary substance expelled by hemipterans) for extra food (Stadler

& Dixon 2005). Therefore, omnivorous ant species may have more associations with mutualists than with other species. Predatory ants may have fewer mutualisms or commensalisms as they are constantly foraging for prey items, and these types of relationships may be too dangerous for myrmecophiles to maintain. However, kleptoparasitic and parasitic myrmecophiles may have evolved successful strategies to exploit predatory ants because their lifestyles require them to infiltrate ant colonies through chemical (Akino 2002; Elgar & Allan 2006), tactile (Hölldobler 1971) and/or audio cues (Sala et al. 2014).

We predicted that certain traits (more spines, stings, larger eyes) would increase beneficial (mutualistic) or benign (commensal) myrmecophiles, while decreasing detrimental (kleptoparasitic and parasitic) myrmecophiles. To test our predictions, we ran predictive models to examine patterns of myrmecophile richness in relation to six variables: subfamily, colony size, number of spines, presence of a sting, eye size, and diet. In addition, we ran similar analyses for each relationship type (mutualisms, commensalisms, kleptoparasitisms, and parasitisms) to better understand how ant traits influence beneficial, benign, and detrimental associations. There are few studies of the ecological roles of these traits in ants (Blanchard & Moreau 2016). This study will allow us to explore whether myrmecophiles play a role in influencing ant traits, and whether they influence richness of myrmecophiles per ant species.

44

3.3 Methods

3.3.1 Data collection

To create the global data set of ant species associated with myrmecophiles, we searched for publications indexed in the ISI Web of Science using the terms:

“myrmecophil*” or "ant associat*" or "ant inquiline" or "synechtran*" or "synoekete*" or "symphile*" or "trophobiont*". These searched words are all associated with myrmecophiles and their relationships with ants (Hölldobler & Wilson, 1990). Of a total of 787 results, we selected those involving only invertebrate myrmecophiles; excluding fungi, microbes, and plants, resulting in 351 usable references (Appendix A). Mites

(Subclass: Acari), nematodes (Phylum: Nematoda) and Collembola (Subclass:

Collembola) were also excluded from the study, because although many of these three invertebrate groups have been reported from ant nests, and some are true myrmecophiles (Rettenmeyer et al. 2010), many published studies do not allow us to conclusively determine their relationship with ants (Parker 2016). Additionally, both mites and collembola are rarely identified to species in the available literature, as noted by Campbell, Klompen, and Crist (2013). Additionally, we only included literature that was peer reviewed, identified the host ant to species (or a morphospecies in a few cases), identified myrmecophile to species or morphospecies, the relationship between ant and myrmecophile, and included a collection locality

(preferably latitude and longitude coordinates, however, broader localities such as a national park were also included, while references with only country of origin were not included).

45

With problems of identification in publications and the need to exclude certain taxonomic groups for our research, we felt it necessary to provide a definition that we used for the word myrmecophile. The word ‘myrmecophile’ is derived from the Greek

‘myrmex’ (ant) and ‘philos’ (loving), so in simple terms, myrmecophile means “ant- lover” (Kronauer and Pierce 2011). Other definitions that are frequently cited are “an organism found in association with ants” (Kistner 1982) and “any organism that is dependent on ants at least during part of its lifecycle” (Hölldobler & Wilson, 1990). To test our hypotheses, however, we followed Parker’s (2016) definition of myrmecophiles, which is “species that capitalize on the social fabric of ant biology”.

3.3.2 Ant and trait definitions

For species names, we used the currently accepted nomenclature for both ants and myrmecophiles derived from antweb.org (2016), antwiki.org (2016), Bolton (1995) and the Hymenopteran Name Server (Johnson 2016). We included subfamily within the analysis to determine if differences in myrmecophile richness between different ant groups may be driven by evolutionary time and relatedness instead of traits of individual ant species. Additionally, using previously constructed phylogenies based on

Moreau et al. 2006, Brady et al. 2006, & Ward et al. 2007, we wanted to visually compare average myrmecophile species richness between related Formicidae subfamilies.

46 Ant species traits were gathered from antweb.org (2016), antwiki.org (2016) and the published sources listed in Appendix B. Colony size for each species was allocated to one of four categories (>1,000 Small, 1,000-10,000 Medium, >10,000-100,000 large,

>100,000 Giant). For missing data, average colony size for the genus was designated or assigned from closely related species. Colony size was chosen over body size because body size can dramatically differ within most ant species, especially ant species that have different castes. Additionally, body size measurements are not easily attained for many of the ant species in our database and therefore we did not test ant body size as a variable within this manuscript. Another ant colony metric, colony mass, may play an important part in myrmecophile richness, with larger ants and larger colonies providing more potential resources. However, colony mass is a rarely reported within the literature, and therefore we did not test it as a variable within this manuscript. The diet of each species was categorised as herbivorous, omnivorous or carnivorous following the definitions and data of Blanchard and Moreau (2016). Spine pairs were counted using images from antweb.org (accessed November 2016) for each species examined, and where there was no image, we used the most common number of spines exhibited by other species in the same genus. Spines were counted only if they were on the thorax and the petiole. Functional stings were recorded as present or absent, and derived from the literature (Blanchard & Moreau 2016). Functional stings were defined as unmodified piercing stings that deliver venom (Blanchard & Moreau

2016). There are some ant genera that have vestigial stingers that no longer act as piercing stings, but deliver droplets of venom, these were not designated as having a functional sting. Eye size was categorised by the number of ommatidia as none, small

47 (1-10 ommatidia), medium (11-100) or large (>100) using images from antweb.org

(accessed November 2016).

3.3.3 Myrmecophile relationship definitions

The relationship types of myrmecophiles were classified into four symbiotic types ranging from beneficial to detrimental associations: mutualist, commensal, kleptoparasite, or parasite. Mutualists were defined as having an association that benefited both myrmecophile and ant host (for example, aphids farmed/protected by ants (Stadler & Dixon 2008), or bees co-habiting with ants in a nest for mutual protection (Sakagami et al. 1989)). Commensal relationships were defined as associations where myrmecophiles benefited, but there were no benefits or detriments to the ant host (for example, moth larva living in middens of an ant colony

(Sanchez-Pena et al. 2003) or crickets living within a colony, but not using ant resources (Komatsu et al. 2009)). For this study, kleptoparasites were associations where myrmecophiles stole food and/or resources from their ant hosts, but did not prey upon them (for example, beetles that steal food from passing ants or are fed by ants (Lencina et al. 2011; von Beeren et al., 2011)). Parasites were defined as myrmecophiles that harmed their hosts, by feeding directly on ants and/or their brood. Organisms that steal food and predate on ants, such as some lycaenid butterfly larva (Thomas & Elmes 2004; Witek et al. 2008) were also classified as parasites.

Associations were cross-checked among different references and the most supported association was used.

48 3.3.4 Statistical analyses

To test the relative importance of subfamily and each of the ant traits (colony size, diet, pairs of spines, presence of a sting, and eye size) in predicting the myrmecophile richness per ant species, we ran negative binomial glms (R package MASS; Venables &

Ripley 2002). We contrasted models of all possible combinations of predictor variables using the function dredge from the R package MuMIn (Barton 2015). Models were first ranked using Akaike’s Information Criteria (AIC; Burnham & Anderson 2011), and then ranked by Akaike weights (wi), which determines the likelihood a model is the best model (Wagenmakers & Farrel 2014). Additionally, only models within the standard confidence set from the best fit model (ΔAIC < 2) were used to derive model average coefficients, standard errors, and relative variable importance (RVI; Barton 2015); models with ΔAIC > 2 were excluded in those calculations as they are considered statistically different from the first model(s) (Burnham & Anderson 2011). Best fit models were visualized with the R package ‘visreg’ (Breheny & Burchett 2013). Relative variable importance (RVI) was then used to determine which variables were most influential on species richness.

For the categorical predictor variables that were found to be influential within our predictive models, we ran Tukey’s post-hoc analyses with R package multcomp

(Hothorn et al. 2008) to test for significant differences among those variables (for example among subfamilies or colony size categories).

To test if ant traits had different effects on the number of myrmecophiles from different symbiotic relationships (mutualism, commensal, kleptoparasite, and 49 parasite), we ran the same analyses previously stated for all myrmecophiles. However, we separated the data set and modelled only ants and ant traits where a specific relationship was present (for example, only ants that had mutualist relationships were modelled to see how their trait affected the number of mutualists they associated with).

In all models, we used the number of published references per ant species as a statistical offset to account for any sampling bias in which a higher species richness of myrmecophiles has been reported for ants that have been more intensively studied.

The number of references per ant species was a significant predictor of myrmecophile species richness per ant (Fig. 3.1A, P < 0.001, df =621) in a generalized linear regression model with a Poisson structure, using R package lme4 (Bates et al. 2014). We chose to use the number of references as a statistical offset instead of designating it as a covariate because statistical offsets reduce the bias of both under and over sampling when using count data, and help to better model the effects of other variables

(Werner & Guven 2007).

3.4 Results

3.4.1 General results

Our synthesis of the literature identified 622 ant species, from eight subfamilies, associated with 1629 myrmecophiles, from a total of 351 references (Table 3.1). On average, there were 4.03 myrmecophile species reported per ant species, and a total of 2557 different associations reported (Table 3.1). The highest reported number of

50 myrmecophiles for a single ant was 193 species for a leaf-cutter ant, Atta mexicana,

with the second-most being 60 species for an army ant, Labidus praedator.

Table 3.1 The number of ant species, myrmecophiles and the average myrmecophile richness for each subfamily of ant recorded in our study. The modelled average was determined using negative binomial generalized linear model with number of references per ant as a statistical offset. Subfamily Ant Reported Average Modelled Number species myrmecophile myrmecophile average of sampled species per ant references species Dolichoderinae 73 150 2.66 1.56 68 Dorylinae 57 374 7.65 3.26 25 Ectatomminae 7 22 3.29 1.69 8 Formicinae 213 440 3.93 1.69 181 Myrmeciinae 13 28 3.23 3.03 2 Myrmicinae 233 721 4.08 2.63 170 Paraponerinae 1 1 1.00 1.00 1 Ponerinae 19 33 2.00 1.21 22 Pseudomyrmecinae 6 5 1.33 1.00 5 Total 622 1629 351

The subfamilies Myrmicinae and Formicinae had the highest number of ant species

included in the study, with over 200 species each, while the other six subfamilies had

fewer than 100 species each (Table 3.1). Ants from the Myrmicinae were also

associated with the most myrmecophile species (731) (Table 3.1). In contrast, ants

from the Pseudomyrmicinae were associated with just five myrmecophiles,

Paraponerinae just one (Table 3.1), and several subfamilies were not recorded having

any myrmecophiles in our literature search (Fig. 3.2).

51 Ants from the subfamily Dorylinae were associated with the highest number of myrmecophiles per ant species (mean = 7.65), followed by those in the Myrmicinae

(4.08). The lowest was the subfamily Pseudomyrmecinae (1.33) myrmecophiles per ant species (Table 3.1). Paraponerinae only had one record of a myrmecophile associated with one species (Table 3.1).

Of the 622 ant species reported, 301 were associated with mutualist myrmecophiles,

161 with commensals, 217 with kleptoparasites, and 177 with parasites. Each ant species was associated with, on average, 2.67 mutualists, 3.99 commensals, 3.29 kleptoparasites and 1.95 parasites.

3.4.2 Differences in myrmecophile rchness between subfamilies

The richness of myrmecophiles per ant species differed significantly among ant subfamilies (Fig. 3.2). Dorylinae and Myrmicinae had the highest modelled averages of myrmecophile richness, 3.26 and 2.63, respectively (Fig. 3.2). Both had significantly higher myrmecophile richness than Dolichoderinae, Formicinae and Ponerinae (P<

0.05; Fig. 3.2). Ectatomminae and Myrmeciinae did not significantly differ in myrmecophile richness with all other ant subfamilies (Fig 3.2). Paraponerinae, having only one species sampled was not compared to the other subfamilies in these analyses.

52

Figure 3.1 Modelled relationships between myrmecophile richness and highly influential variables. a) The relationship between myrmecophile richness and number of references per ant species supporting the need to use references as an offset in further analyses; b) The variation in myrmecophile richness with ant colony size (levels that share a letters do not differ in Tukey’s post-hoc analysis. c) The relationship between the number of pairs of spines and myrmecophile richness. Both a) and c) represent fitted models visualled using the visreg function in R (Breheny and Burchett 2013), with the dotted lines representing 95% confidence intervals.

53

Figure 3.2 Average Myrmecophile richness per ant species within different Formicidae subfamilies, paired with the Formicidae phylogeny based on Moreau et al. 2006, Brady et al. 2006, & Ward et al. 2007. Data are modelled estimates and error bars are 95% confidence intervals from a generalized linear model contrasting myrmecophile associations and ant subfamilies, with a statistical offset of number of references per species. Dot points indicate average myrmecophile richness per ant host. Subfamilies that share a letter do not differ in Tukey’s post-hoc analysis.

54 3.4.3 Predicting myrmecophile richness from ant traits

The best model explaining myrmecophile richness per ant species included the ant traits of colony size, diet and pairs of spines (wi = 0.24; Table 3.2). A second model, not different from the first (wi = 0.17; ΔAIC= 0.66) also included the variable “presence of a functional sting” (Table 3.2). The model averaged Relative Variable Importance (RVI) identified only colony size (RVI: 1.00) and pairs of spines (RVI: 1.00) as influential traits

(Fig 3). Diet (RVI: 0.62), presence of a functional sting (RVI: 0.40) and eye size (RVI:

0.25) were not identified as influential (below the marginal value of 0.70, Fig 3.3). Ant species with giant colonies were associated with almost four-times as many myrmecophile species as ants with other colony sizes (Fig. 3.1b, Tukey’s post-hoc analysis, P < 0.001). Ants with large colonies were modelled to have about 36% higher myrmecophile richness compared to medium (P < 0.001) and small (P < 0.001) colonies, which not differ significantly from one another (P = 0.99; Fig. 3.1b). The richness of myrmecophiles increased as pairs of spines on ants increased (Fig. 3.1c, P <

0.001, df=621).

3.4.4 Variation in importance of ant traits among differing symbiotic relationships

Mutualists: The best model predicting which ant traits influence the number of mutualist myrmecophiles per ant species included the number of paired spines and presence of a sting (wi = 0.69; Table 3.2). These two traits were also identified as the variable of highest relative importance (Fig. 3.3, pairs of spines, RVI = 0.97; sting, RVI =

0.95). Ants with more pairs of spines had higher myrmecophile richness (P= 0.001, df =

55 300; Fig 3.4a). Ants without a functional sting were associated with more species of

mutualists than ants with stings (Fig. 3.4b, Tukey’s post-hoc test, P = 0.01).

Table 3.2 Candidate models using ant traits to predict myrmecophile species richness per species. Models for each mycophile relationship are also presented. Each row contains model variables, number of parameters (K), corrected Akaike Information Criterion (AICc), change in AIC (ΔAIC) from best model, and Akaike weights (wi). Number of references was used as statistical offset in each model. The Null model includes the statistical offset (number of references).

Model number All Myrmecophiles K AICc ΔAIC wi 1 Colony Size + Diet + Spines 8 2579.55 0 0.24 2 Colony Size + Diet + Spines + 9 2580.21 0.66 0.17 Sting 3 Colony Size + Spines + Subfamily 14 2580.74 1.19 0.13 4 Colony Size + Eye Size + Spines + 17 2581.36 1.81 0.10 Subfamily Null 2 2801.60 157.03 0.00 Mutualists 1 Sting + Subfamily 4 1185.87 0 0.69 2 Diet + Sting + Subfamily 6 1189.55 3.68 0.11 Null 2 1815.50 0.00 Commensals 1 Colony size + Spines + Subfamily 13 678.45 0 0.59 2 Colony size + Spines + Sting + 14 680.17 2.04 0.18 Subfamily Null 2 810.13 131.68 0.00 Kleptoparasites 1 Colony Size + Sting + Subfamily 11 893.45 0.00 0.46 2 Colony Size + Spines + Sting + 12 893.36 1.90 0.18 Subfamily 3 Colony Size + Diet + Eye Size + 13 896.12 2.66 0.12 Subfamily Null 2 977.1 83.65 0.00 Parasites 1 Null 2 610.68 0.00 0.24 2 Eye Size 5 610.89 0.22 0.22 3 Sting 3 612.57 1.90 0.09

56

Figure 3.3 Relative Variable Importance (RVI) of predictor variables for number of myrmecophile associations per ant species. Variables are listed according to rank by RVI for each modelled group. The dotted line indicates 0.70 RVI the weighting used to indicate an influential variable.

Commensals: The most strongly supported predictive model of ant traits that influence richness of commensal myrmecophiles included the traits of colony size, pairs of spines, and subfamily (wi = 0.59; Table 3.2). RVI also supported this model, with all three variables being the most influential (Fig. 3.2, colony size RVI = 1.00; spines RVI =

57 0.99; subfamily RVI = 0.88). Ants with more pairs of spines were associated with a higher species richness of commensals (Fig. 4c, P < 0.001). Ant species with giant colonies were associated with more commensal myrmecophiles than other colony size classes (Tukey’s post-hoc analysis, P < 0.001), and large ant colonies had significantly more commensals than medium colonies (P = 0.027), but not smaller ones (Fig 3.4d, P

= 0.376)). Medium and small ant colonies did not differ in the number of commensal myrmecophiles associated with them (Fig. 4d, P = 0.56). Eight subfamilies of ants were associated with commensal myrmecophiles (Fig. 3.4e), with the richness of commensal myrmecophiles within the subfamily Myrmicinae higher than most other subfamilies except for Pseudomyrmecinae, Ectatomminae, and Myrmeciinae (Fig. 3.4e Tukey’s post-hoc analysis, P < 0.05). Ants in the subfamily Myrmeciinae also had more commensals compared to Formicinae (Fig. 3.4e, P = 0.001).

Kleptoparasites: The best model predicting the richness of kleptoparasites included the ant traits of colony size, presence of a sting and subfamily (wi =0.46; Table 3.2), with a second model including colony size, spines, presence of a sting, and subfamily (wi

=0.18; Table 3.2). RVI identified colony size (RVI = 1.00), presence of a sting (RVI = 0.97) and subfamily (RVI = 0.93) as the most important traits influencing the number of kleptoparasitic species per ant species (Fig. 3.2). Ant species with giant colonies were associated with more kleptoparasite species than all other colony sizes (Fig 3.4f, P <

0.001). Ants with large colonies had more kleptoparasites that those with medium sized colonies (Fig. 3.4f, P = 0.002) and ants with medium or small colonies did not differ in kleptoparasitic richness (Fig. 3.4f). Ants with a sting had twice as many kleptoparasitic myrmecophiles as ants without (Fig. 3.4g, P < 0.001). Six ant subfamilies

58 were associated with kleptoparasites (Fig. 3.4h), with ants in the subfamily Dorylinae associated with more kleptoparasitic myrmecophiles than the Dolichoderinae,

Formicinae and Myrmicinae (Fig. 3.4h, Tukey’s post-hoc analysis).

Parasites: The best model to predict the species richness of parasitic myrmecophiles was the null hypothesis (Table 3.2) and thus no ant traits were identified as influencing parasite richness (Fig. 3.2).

59 Figure 3.4 Modelled interactions of myrmecophile species per ant and highly influential variables. a) is the relationship between mutualist richness and ant spine pair; b) shows the differences of mutualist richness and if an ant has a functional sting or not. c) represents ant colony size and commensal richness; d) is the relationship between pairs of ant spines and commensal richness; e) represents the differences between ant subfamilies and commensal richness; f) represents difference in ant colony size and richness of kleptoparasites; g) shows the difference of kleptoparasite richness between ants with and without a sting h) represents the differences between ants within different subfamilies and kleptoparasite richness. a) to h) represent fit models using the visreg function in R(Breheny & Burchett 2013), with 95% confidence intervals. Letters denote significance (P<0.05).

60 3.5 Discussion

3.5.1 Ant traits are strong predictors of myrmecophile richness

Overall, ant traits were strong predictors of the species richness of myrmecophiles associated ants in our global data set of 622 ants and 1629 myrmecophiles. Ant colony size and the numbers of spines were the most influential traits in predicting overall myrmecophile richness, and the richness of myrmecophiles within three of the major types of relationships that myrmecophiles have with their ant hosts (mutualist, commensal, kleptoparasite). Although myrmecophile richness per ant species differed among ant subfamilies, subfamily was associated with the richness of only commensal and kleptoparasitic myrmecophiles. The presence of a functional sting influenced only the richness of mutualistic myrmecophiles, while diet and eye size were never significant predictors of myrmecophile richness.

Ants with larger colonies supported a higher richness of associated myrmecophiles, with the species having the largest colonies (>100,000 ants) supporting more than four-times the myrmecophiles than those ant species with smaller colonies (Fig. 3.1b).

These results support the general hypothesis that organisms with a larger body size would support more symbionts (Price 1980; Ezenwa et al. 2006) and previous research with myrmecophilous beetles that demonstrated higher richness with larger ant colony size (Päivinen et al. 2003). Larger ant colonies offer more resources, in the form of workers (as a food source and as protection), larger nest sizes (Valverde et al. 2014), stored food, and waste (Holldobler & Wilson 1990), allowing for a higher density of myrmecophiles. Moreover, larger ant colonies are easier to locate than to smaller

61 ones, enabling easier colonization by dispersing myrmecophiles (Pӓivinen et al. 2003).

The theory that larger colonies are providing extra resources is supported by our finding that both commensal and kleptoparasitic myrmecophiles had highest richness for ants with larger colonies. Commensal myrmecophiles typically exploit ant nests for their regulated environment, the added protection from predators, and consuming ant waste. Kleptoparasites however, require reliable food to steal (Iyengar 2008), either directly or indirectly from ants. Ants with larger colonies would have more food and better able to support a higher number of organisms utilizing it.

Ants with more spines were associated with a greater richness of myrmecophiles.

Spines on the thorax or petiole are a potential defense against predators (Ito et al.

2016), however, the role of spines and other morphological traits in mediating other interactions such as those with myrmecophiles, remains poorly understood (Dornhaus and Powell 2010). As more spines could make ants less palatable to predators, myrmecophiles could gain an added benefit of associating with ants that are better defended. This is supported by our finding that the richness of both mutualist and commensal myrmecophiles increased with the number of spines, and that both relationships can use ants for defensive purposes. Experiments on how ant spines play a role in ant defense against predators, competitors (other ants), and what role they may play in myrmecophile associations would be useful in further understanding this pattern.

Ant species lacking a functional sting were associated with a higher richness of mutualist myrmecophiles than ants with functional stings. Most ant-myrmecophile

62 mutualisms involve ants farming Lepidoptera or Hemiptera for honey-dew (food) in return for protection (Holldobler & Wilson 1990). The sting and its associated chemicals have been suggested as energetically costly for use against both prey or in defense (Blanchard & Moreau 2016). Consequently, defending a potential mutualist may not be as beneficial compared with just treating it as a prey item. Ants without stings often use chemical defense (usually formic acid), which is not as energetically taxing, and can be used to spray an enemy from afar. This form of defence may thus be less of an investment in protecting mutualist myrmecophiles than a sting that requires relatively close contact. Conversely,ants with stings had twice as many kleptoparasites than ones without. This may indicate that it is easier to steal from ants with stings . To test this, more work comparing ants with and without stings and surveying their interactions with mutualists and kleptoparasites is needed.

The eye-size of ants was not influential in predicting myrmecophile richness. This may be because ant eyes are used more for avoiding vertebrate predators than for focusing on associated invertebrates (Blanchard & Moreau 2016). Additionally, ants may not have the visual acuity to differentiate between an ant and a myrmecophile that looks like an ant. Myrmecophiles that mimic ants in shape are usually considered to do so as camouflage from vertebrate predators rather than to trick the ants (McIver &

Stonedahl 1993). As ants also use chemical and tactical communication, it may be that if myrmecophiles “trick” ants through these means, visual cues may not matter as much in the ant world.

63 3.5.2 A few ant subfamilies rich in myrmecophiles

Two ant subfamilies, Myrmicinae and Dorylinae, were modelled to have the highest myrmecophile richness compared withother subfamilies. Myrmicinae is the most diverse group of ants, ~7300 (Ward et al. 2014: Antwiki 2017), which is morphologically varied, and exhibits a wide range of lifestyles from giant leaf-cutter ant colonies in the genus Atta, to small cryptic colonies of Temnothorax (Benoit 2013;

Ward et al. 2014). This wide range of diversity is probably a main driver of commensal associations. Additionally, Myrmicinae has a long evolutionary history, ~100 million years, but most major crown species have evolved recently, within the last 52-71 million years (Ward et al. 2014), this rapid evolution may have potentially played a role in myrmecine species having high myrmecophile richness. Dorylinae is the army ant subfamily, with a less diverse set of species compared to many subfamilies (805 species) and an older set of crown group species, ~87 million years (Brady et al. 2014), so it is not a rapidly evolving group of ants. Although evolutionary history may not be as influential in myrmecophile richness of Dorylinae species, life history and traits potentially are. Dorylinae are known for their large colonies that raid for food, and are commonly on the move (Hölldobler & Wilson 1990). This legionary lifestyle may explain why Dorylinae species have so many myrmecophiles, especially kleptoparasites, which are able to infiltrate nomadic ant colonies easier than subterranean colonies.

64 3.5.3 Parasite enigma

Our models did not find any influential variables that determined parasitic myrmecophile richness. In our other study (see Chapter 4), parasites had a narrow host range, which indicates that parasites need to be specialized for their host. Additionally, as parasites are expected to have detrimental effects on an ant colony (because they feed directly on ants and larva), they may only be able to support a limited number of parasitic species. Moreover, other ant traits that we did not examine such as chemical recognition or behavioural traits (grooming for example) may be drivers of parasite richness. More research on how ants interact with parasites and in-depth look into chemical communication traits within ants, may allow us to better understand parasite species richness within the Formicidae.

3.5.4 Conclusion

We present here what we believe is the first global analysis of myrmecophile richness per ants species based on ant traits. Myrmecophile richness was driven by both subfamily, colony size and defensive traits (such as spines and stings). In general, the larger the ant colony, the more spines an ant species has, the richer the myrmecophiles. These findings show that host traits are important drivers of symbiont richness, especially for ant-myrmecophile associations.

65 Publication details: Glasier James R.N., Poore Alistair G.B., Eldridge David J. (in prep). Ant traits determine richness of myrmecophiles associated with individual ant species.

66 Chapter 4

Do mutualistic associations have broader host ranges than neutral or antagonistic associations? A test using myrmecophiles as model organisms

4.1 Abstract

Symbiotic associations are found across all kingdoms of life and are integral to ecosystem structure and function. Central to understanding the ecology and evolution of symbiotic relationships is an understanding of what influences host range; the number of host species that a symbiont can utilize. Despite the importance of host specificity among symbionts, relatively little is known about how the relationship that a symbiont has with its host influences its host range. Additionally, contrasts among interaction types often involve diverse groups of unrelated host species. To test how host specificity varied with interaction type, we used a global synthesis of over 1600 species of myrmecophiles, those organisms that have symbiotic associations with ants.

We used an indexed literature search to collate known myrmecophile species and their hosts, and to determine how two degrees of dependence (facultative, obligate) and four types of relationships (mutualism, commensalism, kleptoparasitism, and parasitism) between myrmecophiles and their hosts influence host range. Our synthesis showed that, overall, myrmecophiles exhibited a high degree of host specialization, and that facultatively dependent myrmecophiles had broader host ranges than those with obligate interactions. Myrmecophiles with mutualistic relationships had broader host ranges than neutral or antagonistic relationships.

Additionally, lepidopteran myrmecophiles exhibited broader host range patterns than other taxa. The results have important implications on how symbiotic associations are

67 understood, with positive relationships (mutualisms) promoting broader host range, and antagonistic relationships (parasitism) promoting narrow ones.

4.2 Introduction

Symbiotic associations have an important influence on ecosys tem structure and function, and have been credited with driving global diversity (Thompson 1994; Poulin

2004). These close associations between organisms are found in all kingdoms of life at differing degrees of dependence, with species facultatively associated with or obligatory dependent on their hosts and involving a wide range of relationship types

(mutualisms, commensalisms, and parasitism). Associations can be mutually beneficial to both symbiont and host (mutualisms), beneficial to the symbiont with unsubstantial effects on host (commensalisms), or antagonistic, in varying degrees, to host while benefiting the symbiont (parasitism) (Boucher et al. 1982).

Central to understanding the ecology and evolution of symbiotic interactions is predicting what factors promote or constrain the number of host species used by a symbiont. Understanding the costs and benefits of host specificity in species interactions has been a major aim of research into plant-herbivore, plant-pollinator, host-parasite, and other symbiotic interactions (Futuyma & Moreno 1988; Poulin et al.

2011; Kamiya et al. 2014). Symbionts associated with fewer hosts are often more morphologically or behaviourally specialized, and better able to utilize host resources than those with multiple hosts, but potentially have reduced availability of hosts in space and time (Thompson 1994; Thomas & Elmes 2004). A reduced host availability

68 becomes more common with coevolution of symbionts and their hosts, leading to highly specialized traits for the exploitation of particular host resources (Proctor &

Owens 2000; Krasnov et al. 2001). Consequently, facultative symbionts, tend to have broader host ranges than obligates, which rely on their associations to survive.

The type of relationship between an organism and its hosts may also affect host range.

Contrasts of positive (mutualistic) and antagonistic (parasitic) relationships, however, have often involved comparisons among taxonomically dissimilar hosts, making it difficult to test the role of relationship type. Many mutualistic relationships such as pollination or seed dispersal, show a low degree of host specificity for the pollinator or disperser (Thompson 1994). However, other interactions have shown that coevolution of mutualist symbionts and hosts can result in highly specific and narrow host ranges

(Boucher et al. 1982; Kawakita et al. 2010). For example, the pollinating fig wasps have a narrow host range towards their host Ficus tree (Ramirez 1970; Machado et al. 2005);

Specialist anemone fish may also exhibit a narrow host range towards their mutualist sea anemones (Ollerton et al. 2007). Parasitic associations often favour narrow host ranges, along with morphological and/or behavioural specialisation, as adaptations to overcome host defenses are needed (Price 1980; Schär & Voburger 2013). However, broad host ranges can also be found in a wide range of free-living parasitic associations such as avian brood parasites (Davies & Brooker 1989), kleptoparsitic birds (Brockmann

& Barnard 1979; Thompson 1994), cookiecutter sharks (Isistius sp.) (Papstamatiou et al. 2010), and vampire bats (Desmodontinae) (Voigt & Kelm 2006). Comparisons of wide-ranging associations between different organisms and their hosts make it difficult to determine how relationship type may be influencing host range.

69

Myrmecophiles, those organisms associated with ants (Hymenoptera: Formicidae)

(Kistner 1982; Kronauer & Pierce 2011), provide an accessible model to examine how host range varies among a wide range of symbiotic associations within a single group of hosts. Myrmecophiles exhibit a wide spectrum of association types, are taxonomically diverse, and all use similar hosts (ants) (Kistner 1982; Hölldobler & Wilson 1990). Ants are abundant, ubiquitous and ecologically dominant in most terrestrial ecosystems, and provide a wide set of resources for myrmecophiles such as homeostatic colonies, protection from predators, stored food and potential prey items (brood and workers).

Ants aggressively defend their colonies and resources, and myrmecophiles must use a variety of tactics to evade, avoid, or placate their hosts (Hughes et al. 2008). In simple terms, myrmecophiles either have to attract ants or overcome ant defences to associate with their hosts. Attracting ants for many mutualis tic myrmecophiles involves providing honeydew (sugary secretions) in exchange for protection (Kaminski et al.,

2010; Tegelaar et al. 2012). This relationship involves a cost of honeydew production but may not limit the number of ant hosts that can utilize this widely acceptable carbohydrate resource (Kindlmann et al. 2007). Conversely, overcoming ant defenses through mimicking chemical cues (Akino 2002; Elgar & Allan 2006; Witte et al. 2009), tactile communications (Hölldobler 1971) and/or audio cues (Sala et al. 2014) is often much more specific to particular ant taxa. The cost of overcoming ant defenses, therefore, may limit the number of potential hosts (von Beeren et al. 2011). Using myrmecophiles as a model allows us the opportunity to examine symbiotic associations on a broader scale and determine how dependence and relationships may drive host range.

70

Here we report a global synthesis of the host range of myrmecophiles of all symbiotic relationship types. We compiled a database of 350 published studies on 1605 myrmecophile species and quantified how dependence, type of relationship, and taxonomic group vary with host range. We test the predictions that (1) facultative myrmecophiles would have broader host range (number of associated ant species) compared to obligates, as they do not require ants to survive, but would be expected to opportunistically associate with numerous ant species; and (2) beneficial associations would have a broader host ranges than antagonistic ones, as hosts would have more defenses against negative relationships. For each dependence and relationship type, we tested whether patterns were consistent across the major taxonomic groups of myrmecophiles.

4.3 Methods

4.3.1 Data compilation

We searched for publications indexed in the ISI Web of Science using the terms: myrmecophil* or "ant associat*" or "ant inquiline" or "synechtran*" or "synoekete*" or "symphile*" or "trophobiont*". Searched words are all associated with myrmecophiles and their relationships with ants (Hölldobler & Wilson 1990). Of a total of 787 results, we selected those involving only invertebrate myrmecophiles; excluding fungi, microbes, and plants. Mites (Subclass: Acari), nematodes (Phylum: Nematoda) and collembola (Subclass: Collembola) were also excluded from the study as while many species of these three invertebrate groups have been reported from ant nests,

71 and may be true myrmecophiles (Rettenmeyer et al. 2011), many published studies do not allow us to conclusively determine their relationship with ants (Parker 2016).

Additionally, both mites and collembola were rarely identified to species in the available literature (Campbell et al. 2013).

With problems of identification in references and the need to exclude certain taxonomic groups for our research, we felt it necessary to provide a definition that we used for the word myrmecophile. Myrmecophile is from the Greek ‘myrmex’ (ant) and

‘philos’ (loving), so in simple terms, myrmecophile means “ant-lover” (Kronauer &

Pierce 2011). Other definitions that are frequently quoted are “an organism found in association with ants” (Kistner 1982) and “any organism that is dependent on ants at least during part of its lifecycle” (Hölldobler & Wilson 1990). To test our hypotheses however, we followed Parker’s (2016) definition of myrmecophiles which is “species that capitalize on the social fabric of ant biology”.

Studies we included in our analysis were restricted to our definition of a myrmecophile, and those that reported the species name for each myrmecophile, the type of relationship, the degree of association, sample location, and host ant species. Further studies were added by examining the reference lists from each paper found. Under these search criteria, we compiled a data set derived from 350 published studies.

Additionally, we made the effort to correct for nomenclature synonyms for both ants and myrmecophiles to the best of our ability.

72 4.3.2 Contrasts in host range among myrmecophile taxa, reliance and relationship

types

To test the hypothesis that host range (number of ant species) varied among myrmecophile taxa, we contrasted the number of ant species associated with each myrmecophile species among orders. Host number for each species was determined by summing all host records from the examined literature. Host range was contrasted among orders using a generalized linear model, with a Poisson error structure and the number of references per myrmecophile species as a statistical offset. This statistical offset was used instead of a covariate, to account for the observation that taxa which were highly studied tended to have more host species (Werner & Guven 2007). A statistical offset controls for sample bias, reduces the influence that the number of references sampled has on our myrmecophile species richness, and helps to better model the effects of other variables (Werner & Guven 2007). The significance of the predictor variable in the generalized linear model was determined with an analysis of deviance contrasting the two models with and without the predictor variable

(providing the likelihood ratio statistic, G2). Maximum likelihood estimates for each level of the predictor variable and 95% confidence intervals obtained from bootstrapping were obtained for visualizing variation among and within orders. All analyses were conducted with the R package lme4 (Bates et al., 2014). To control for some species being over-studied (such as species in the genus Phengaris, Order

Lepidoptera: Family Lycaenidae) every myrmecophile with five or more studies (a total of eight species) was designated to have only five studies (the asymptote of the sigmoidal relationship of the number of studies in relation to number of hosts).

73 Each myrmecophile species was categorized by their dependence: facultative or obligate, based on information in relevant studies. A facultative dependent was defined as an invertebrate that may associate with ants, but does not need to, to survive (for example: the aphid Aphis fabae cirsiiacanthoides Scopoli, 1763 (Stadler & Dixon 1999) or the caterpillar Parrhasius polibetes (Lycaenidae) (Stoll 1781) (Kaminski & Rodrigues

2011) which may be tended by ants, but are able survive without ant association; or many beetles of the family Latriidae which may seek refuge in ant nests, but do not have to, to survive (Lapeva-Gjonova & Rücker 2011)). An obligate dependent was defined as an invertebrate that required an association with ants to survive (for example: the highly co-evolved obligate mutualisms between mealybugs

(Pseudococcidae) and Acropyga ants, where both need one another to survive (Smith et al. 2007); or the spider Cosmophasis bitaeniata (Salticidae) (Keyserling 1882), which has evolved to almost exclusively eat the larva of weaver ants, Oecophylla smaragdina

Fabricius, 1775 (Edgar & Allen 2006)). To test the hypothesis that obligate myrmecophiles are involved in more specialized interactions, we contrasted host range between facultative and obligate myrmecophiles using generalized linear models (as above). This was done for all myrmecophile species and also within the five most speciose orders of myrmecophiles (Diptera, Coleoptera, Hemiptera, Hymenoptera and

Lepidoptera).

Myrmecophiles were placed along a gradient ranging from positive to negative association using four relationship types: mutualist, commensal, kleptoparasite, or parasite. Mutualists were defined as having an association that benefited both myrmecophile and ant host (for example, aphids farmed/protected by ants (Stadler &

74 Dixon 1999), or bees co-habiting with ants in a nest for mutual protection (Sakagami et al. 1989)). Commensal relationships were defined as associations where myrmecophiles benefited, but there were no benefits or detriments to the ant host

(for example, moth larvae living in middens of an ant colony (Sanchez-Pena et al. 2003) or crickets living within a colony, but not using ant resources (Komatsu et al. 2009). For this study, kleptoparasites were associations where myrmecophiles stole food and/or resources from their ant hosts, but did not prey upon them (for example, beetles that steal food from passing ants or are fed by ants (Lencina et al. 2011; von Beeren et al.

2011)). Parasites were defined as myrmecophiles that harmed their hosts, by feeding directly on ants and/or their brood. They may also be organisms that steal food and predate on ants, such as some lycaenid butterfly larva (Thomas & Elmes 2004; Witek et al. 2008). Associations were cross-checked among different references and the most supported association was used.

4.4 Results

4.4.1 The distribution of myrmecophiles among invertebrate taxa and relationship

types

Our literature review identified 1605 myrmecophile species from 127 families and 20 orders of invertebrates, derived from 4399 records in 350 publications (Table 4.1).

Species from the order Coleoptera comprised ~64 % of reported species associated with ants (Table 4.1). Other speciose orders with 50 or more species of myrmecophiles were the Diptera, Hemiptera, Hymenoptera and Lepidoptera (Table 4.1). The majority of species (~90 %) were only reported from one study. The reported species were

75 evenly distributed among facultative (47% of species) and obligate (53%) myrmecophiles (Fig. 4.1). Kleptoparasitic relationships were most commonly reported

(36% of species), while parasitic relationships were least reported (12.5%, Fig. 4.1).

Figure 4.1 The number of myrmecophile species exhibiting different degrees of reliance on their ant hosts and type of relationships with ants.

4.4.2 Contrasts of host range among myrmecophile taxa, dependence and

relationships

Most myrmecophiles were reported from only one ant host (~80 % of species), but the number of host species ranged from 1 to 20 (Fig. 4.2) and myrmecophiles, on average, were associated with 1.55 ± 0.04 (mean ± SE) host ant species. The number of ant hosts per myrmecophile species varied significantly among orders (Fig. 4.3, G2 =

212.76, df = 19, P < 0.001). Within the five most speciose (>50 species of myrmecophiles) orders Lepidoptera and Hemiptera had ~54% more hosts compared to the other three orders (G2 = 177.19, df = 4, P < 0.001). The host range of the Diptera,

76 Coleoptera, and Hymenoptera did not differ (Fig. 4.3).

Across all species, facultative myrmecophiles were associated with ~75% more hosts than obligate myrmecophiles (Fig. 4.4, G2 = 51.55, df = 1, P < 0.001). Host range varied with dependence in the Lepidoptera, with facultative species using, on average, about two more host species than obligate species (G2 = 35.81, df = 1, P < 0.001). Within the

Hemiptera, facultative hemipterans used a greater number of hosts than obligates (G2

= 31.14, df = 1, P<0.001). Host range did not differ between facultative and obligate myrmecophiles in the Diptera (G2 = 0.03, df = 1, P = 0.853), Coleoptera (G2 = 1.71, df =

1, P = 0.191), or Hymenoptera (G2= 0.07, df = 1, P = 0.788).

The host range of myrmecophiles significantly varied with relationship type (Fig. 4.5,

G2= 170.55, df = 3, P< 0.001). Mutualists had at least ~61% more hosts than all other relationship types and the host range of commensals, kleptoparasites, and parasites did not differ from one another (Fig. 4.5). Host range also varied with the type of relationship in the Lepidoptera (G2= 44.20, df = 3, P<0.001). Mutual and commensal lepidopteran myrmecophiles had, on average, about two more host species than kleptoparasites and parasites (Fig. 4.5). Relationship type did not vary with host range within the Coleoptera (G2= 6.6, df = 3, P = 0.085), Diptera (G2 = 0.10, df = 2),

Hemiptera (G2 = 2.27, df = 1, P = 0.132), or Hymenoptera (G2 = 0.14, df = 1, P =0.831).

77 Table 4.1 The orders of invertebrates that are known myrmecophiles, with the number of species and families of myrmecophiles per order, the number of species for each type of interaction, and the number of references per order. Dependence Relationship type Order Species Families Facultative Obligate Mutualist Commensal Kleptoparasite Parasite References Coleoptera 1028 35 483 545 2 396 538 92 112 Hemiptera 289 25 189 100 282 0 0 7 79 Lepidoptera 70 5 20 50 39 4 17 10 81 Diptera 57 6 2 55 0 4 5 48 30 Hymenoptera 51 16 4 47 5 3 1 42 21 Isopoda 23 8 12 11 0 23 0 0 12 Orthoptera 16 2 1 15 0 6 10 0 20 Polydesmida 14 4 14 0 0 14 0 0 4 Araneae 9 7 1 8 1 6 0 2 16 Blattodea 9 4 4 5 0 6 3 0 8 Geophilomorpha 9 3 9 0 0 9 0 0 1 Thysanura 9 3 1 8 0 5 4 0 11 Lithobiomorpha 6 1 6 0 0 6 0 0 1 Julida 4 1 4 0 0 4 0 0 2 Pseudoscorpionida 4 2 1 3 0 4 0 0 3 Isoptera 3 1 3 0 0 3 0 0 2 Dermaptera 1 1 1 0 0 1 0 0 1 Neuroptera 1 1 1 0 0 1 0 0 1 Polyxenida 1 1 1 0 0 1 0 0 1 Thysanoptera 1 1 1 0 0 1 0 0 1 Total 20 1605 127 762 845 331 497 578 201 350

78

Figure 4.2 The distribution of host breadth (number of ant species) for all species of myrmecophile.

79

Figure 4.3 The number of host ant species per myrmecophile species for the five most speciose orders of myrmecophiles. Note: Data are estimates and 95% confidence intervals from a generalized linear model contrasting host range across orders. Sample sizes (numbers of myrmecophile species) are given above the x-axis.

80

Figure 4.4 Differences in the number of host ant species per myrmecophile species between facultative and obligate interactions. Note: Data are estimates and 95% confidence intervals from a generalized linear model contrasting host range between interaction types, for all species and for each of the most five most speciose orders. Sample sizes (numbers of myrmecophile species) are given above the x-axis.

81

Figure 4.5 Differences in the number of host ant species per myrmecophile species among mutualistic, commensal, kleptoparasitic and parasitic interaction types. Note: Data are estimates and 95% confidence intervals from a generalized linear model contrasting host range between interaction types, for all species and for each of the most five most speciose orders. Sample sizes (numbers of myrmecophile species) are given above the x-axis.

4.5 Discussion

Our global analysis of the host use of myrmecophiles revealed four general conclusions. First, myrmecophiles are highly diverse, but exhibit narrow reported host ranges (Fig. 4.1). Second, as expected, facultative myrmecophiles had a broader host

82 range than obligates, however, this has not been demonstrated often in the literature and this finding adds more support for this “known” pattern. Third, mutualistic associations had a greater host breadth than other relationship types. Lastly, orders that had primarily mutualistic taxa (Lepidoptera and Hemiptera) exhibited broader host ranges than orders with taxa that did not.

4.5.1 Host range of myrmecophile orders

Our synthesis revealed a high diversity and wide range of invertebrate taxa closely associated with ants. Insects (Insecta) are the most speciose group of myrmecophiles, but there are also taxa from the Crustacea, Arachnida, Diplopoda and Chilopoda. These myrmecophiles have a wide range of associations with their ant hosts, from mutualisms where myrmecophiles provide honey dew in return for protection by their ant hosts, to parasites living within nest feeding on ant brood. Despite local diversity of ants being high in most environments, myrmecophiles in general have narrow host ranges, with the vast majority of species having been reported to associate with only one ant species.

We found that lepidopterans had a broader host range, of about two ant species per lepidopteran species, than the other orders of myrmecophiles, except hemipterans.

Differences in life history traits among orders might explain this difference. For example, lepidopterans associate with ants as caterpillars, and spend a large part of their larval stage feeding on host plants (Fielder 1996). As the food plant is a more important resource than protection from ants, the ability to associate with multiple

83 host ant species across the range of the host plant(s) would be more advantageous than specializing towards associations with only one ant species. Several studies indicate support for the notion that different lineages of the same species will utilize different host ants depending on locality (Witek et al. 2008; Eastwood et al. 2006). This localized specialization may be a major factor influencing broader host range of lepidopterans.

Similar to lepidopterans, most hemipteran myrmecophiles are mutualists, and they show a broader host range than the other orders of myrmecophiles, but on average, a narrower host range than lepidopterans. The difference between lepidopterans and hemipterans may be that aphids are “farmed” by ants, thus leading to potential coevolution between hemipteran myrmecophiles and aphids. Ants are able to control hemipteran myrmecophiles, resulting in specialization of not only the myrmecophile but also the host (Maschwiz & Hänel 1985; Schneider & LaPolla 2011). Additionally, certain species of ants may monopolize aphid resources, excluding other ants from hemipteran colonies and reducing potential host interactions (Delabie 2001; Blüthgen et al. 2006). Finally, many ant species are obligate hemipteran farmers (Maschwitz &

Hänel, 1985; Oliver et al. 2008; Schneider & LaPolla 2011). These specialized associations potentially drive speciation among both hemipterans myrmecophiles and ant hosts (Oliver et al. 2008).

The similar and narrow host ranges of myrmecophiles in the Diptera and Hymenoptera may have resulted from the fact that most are ant parasites. Moreover, they are parasitoids, laying their eggs either in adult workers or ant brood (Porter, 1998;

84 Loiacono et al. 2013). To penetrate a host ant colony, and or host ant individual (when an organism is an internal parasite) requires a high degree of specialised adaptations

(behavioural, chemical) to overcome ant defence systems, and therefore may limit host breadth of a species (Thompson, 1994). A narrow host range was also observed in the

Coleoptera, but this group had a diverse set of relationships with ants. Their use of a low number of host ant species may relate to abilities to better utilize particular host resources (Thompson, 1994) or being limited by ant defensive mechanisms (von

Beeren et al. 2011). Overall, taxa with narrow host ranges are likely more efficient at using their particular ant hosts as resources, and are most likely specialized, behaviourally or physically, to nullify their ant host’s defenses.

4.5.2 Host range of dependence and relationship types

Consistent with our predictions, we found that facultative myrmecophiles have broader host ranges than obligates. Facultative associations are often opportunistic in nature, relying on chance encounters of symbionts interacting with a host (Rodrigues et al.

2010). The ability to interact with more ant species would increase the chance of encountering hosts and therefore benefit a facultative myrmecophile. The narrower host ranges observed in obligate myrmecophiles are likely to be because of beneficial adaptations that better utilize host resources. Coevolution between obligate symbionts is likely to increase the dependence on chosen hosts and lead to narrower host ranges

(Fleming & Holland 1998; Machado et al. 2005; Campbell et al. 2013). Although this finding is not unexpected, few studies have quantifiably demonstrated host range differences between facultative and obligate symbionts.

85

Our results are consistent with prediction that myrmecophiles involved in mutualistic interactions would have broader host ranges than those in antagonistic interactions

(kleptoparasites and parasites). While some mutualistic interactions are highly specialised, broad host ranges among some obligate mutualist have been reported. For example, obligate photosynthetic dinoflagellate symbionts use a wide range of host corals as structural hosts (Baker 2003) and hummingbirds can pollinate a wide range of flowers and in return, harvest nectar (Hoeksema & Brun 2000). As mutualists have

~61% broader host range than other relationships, it is apparent that they are able realize a wider potential niche than other myrmecophiles.

We predicted that parasitic myrmecophiles, the symbionts that are most antagonistic to ants, would have the narrowest host range. The basis of our prediction was that, as parasites feed directly on ants or ant brood, ants would likely evolve defensive mechanisms to prevent parasitic attacks, forcing the parasites to utilize a narrower range of host species so that resources were more readily available. However, we found that kleptoparasites and commensals had host ranges equally narrow as parasitic myrmecophiles. There are several explanations to explain these results. Ants use a wide range of chemical, tactile, visual, and audio cues to recognize nest mates and larvae (Akino 2002; Jackson & Ratnieks 2006). As different ant species use different cues, and cues within species can vary, adaptations to overcome these defences may limit the number of host associations a myrmecophiles is able to have. It may be most beneficial to allocate resources to overcome defensive cues of a limited number of ant species, rather than utilizing resources to associate with a multitude of hosts.

86

Interestingly, myrmecophiles that were commensal with ants shared similar host ranges as kleptoparasites and parasites. This contrasted with our prediction was that neutral associations would exhibit broader host ranges than antagonistic associations.

Commensal myrmecophiles exhibit a wide range of life styles associated with ants. For example, they may overwinter in ant nests (Sanders 1964), live in waste middens of a colony (Rettenmeyer et al. 2011), or inhabit the galleries of a nest (Gray 1971). These differing life styles make it difficult to determine what unifying factor might be limiting the host range of commensals. It may also be that commensals are equally limited by ant defenses as kleptoparasites and parasites.

It should be noted that the number of associations and nature of interactions, for many species of myrmecophiles have not been extensively studied (Mynhardt 2013).

Consequently, variation in host range and patterns among interaction types are not fully understood and have the potential to change with further investigation of particular groups. Moreover, it has also been suggested there could be over 80,000 extant myrmecophilous species (Schönrogge et al. 2000). The search parameters for our study were set out to find references that provided direct evidence of relationships between the myrmecophiles and their host ant(s), as such the species richness of myrmecophiles considered here, while high (n = 1605) remains a small sample of the potential diversity. The limited information on individual myrmecophile species (~90% with only one citation), signifies the need for more research on these ant symbionts, specifically on biology and interactions with their ant hosts (Mynhardt 2013).

87 Given that host range of invertebrates can be related to study effort (Poore et al. 2008), we used the number of publications per myrmecophile species as a statistical offset in our analyses to help account for the possible effects of variation in sampling effort.

While we are confident that the patterns of host range across orders and interaction types are not confounded by sampling effort, the low number of studies for most species of myrmecophiles (Fig. 4.1) indicates that our estimates of host range are likely at a lower limit. Clearly more research is needed, not just for groups of myrmecophiles but also for particular species to increase our understanding of myrmecophilic associations.

Our global synthesis indicates that facultative associations promote broader host ranges than obligate interactions, and that beneficial (mutualistic) associations promote broader host ranges than neutral (commensal) and antagonistic

(kleptoparasitic and parasitic) associations. Our study has broad implications for the evolution of symbiotic associations. As ants live in highly guarded social societies, most myrmecophiles exhibit narrow host ranges in order to exploit the resources associated with those societies. By studying myrmecophiles, we have a better understanding of how differences in host dependence and relationship, influences host range in symbiotic associations.

Publication details Glasier James R.N., Poore Alistair G.B., Eldridge David J. (in prep). Do mutualistic associations have broader host ranges than neutral or antagonistic associations? A test using myrmecophiles as model organisms.

88 Chapter 5

Variable effects of current and historic livestock grazing on above- and below- ground ant communities in a wooded dryland

5.1 Abstract

Grazing by European livestock over the past two centuries has had marked effects on

Australian plants, soils and biota, given Australia’s short evolutionary history of grazing. Most research on grazing effects has focussed on current grazing effects on aboveground taxa. Here we focus on the effects of both grazing history (long ungrazed, recently ungrazed, currently grazed) and grazing intensity (using distance from water as a proxy) on both aboveground and belowground ant communities in a semi-arid woodland. We expected that ant 1) community composition would vary with grazing history, 2) richness would follow a logistic relationship with increasing grazing intensity, and 3) above- and belowground communities would show similar responses to grazing. We found that grazing history had a stronger effect than grazing intensity on aboveground ant communities, but there were no effects on belowground ants.

Aboveground ant richness was greatest at currently grazed sites and least at long ungrazed sites. There were no effects of grazing intensity on above- or below-ground total ant richness, but increased grazing intensity increased the richness of aboveground Hot Climate Specialists only. Trends in ant richness with grazing intensity were poorly reflected by a logistic relationship. Grazing history and grazing intensity had strong suppressive effects on aboveground richness via reductions in biocrust or litter cover. Our results indicate that both grazing history and intensity have marked effects on ant richness and composition, but below ground communities were largely

89 unaffected. Belowground ant communities are unlikely to be affected by current livestock grazing.

5.2 Introduction

Disturbance is a major driver of changes in species richness and diversity (Houston

1973; Mackey & Currie 2001). The intensity and frequency of disturbances are known to have major effects on ecosystem structure, function and composition, and can influence abundance, richness and distribution of biota (McCabe & Gotelli 2000;

Mackey & Currie 2001). Different models have been used to describe the response of ecosystems to increasing disturbance. Foremost among these, the Intermediate

Disturbance Hypothesis, predicts that diversity will peaks at moderate levels of disturbance (Connell 1978), while the Mass Ratio Hypothesis predicts that diversity will peak under high intensity or frequency of disturbance, and decline and stabilise as disturbance decreases (Kershaw & Mallik 2013). In terrestrial systems grazed by

European herbivores, the piosphere effect (sensu Lange 1969) predicts that changes in species diversity and abundance emanating from livestock watering points follow a logistic pattern (Lange 1969; Graetz & Ludwig 1978). The response of particular biota to disturbance will depend on the form of the disturbance, its frequency, and the capacity of taxa to resist (resistance) or recover from (resilience), disturbance (Mackey

& Currie 2001; Kershaw & Mallik 2013).

The best known and probably most widely reported form of human-induced disturbance on Earth is the grazing of European livestock. Grazing sustains human

90 cultures worldwide, and supports millions of people, particularly in developing nations, providing essential goods and services and the potential to accumulate capital. The effects of grazing, however, are complex, with impacts depending on climate (Díaz et al., 2007), evolutionary history, and type and intensity of grazing (Lunt et al. 2007;

Eldridge et al. 2011). The combined effects of herbivory and the physical effects of animal trampling can lead to long-term, often deleterious effects on ecosystems by, for example, reducing spatial heterogeneity (Fuhlendorf & Engle 2001), altering vegetation composition (Yates et al. 2000), and reducing soil physical status and chemical function

(Lunt et al. 2007; Eldridge et al. 2013). These effects are predicted to be strongest in environments with a short evolutionary history of grazing by livestock, such as in

Australia (Cingolani et al. 2010), where European herbivores have grazed for les s than two centuries. The imposition of a European style of grazing has been accompanied by an increase in the densities of native herbivores (kangaroos, Macropus spp.) due to increases in water and the reduction in populations of natural predators such as dingoes. This has resulted in relatively high levels of total grazing pressure over much of the area grazed by livestock. Currently, cattle and sheep grazing occurs across about

305 million hectares of land in Australia (ABS 2015), and overgrazing has marked effects on ecosystems, their processes and resident biota (Eldridge et al. 2016). Few studies however, have attempted to separate the long-term (legacy) effects of grazing resulting from historical influences from more recent effects due to current differences in grazing intensity (though see Lunt et al. 2007). This is important because contemporary differences in grazing intensity may fail to explain changes due to grazing in environments with a long history of past overgrazing.

91 We used changes in ant community composition and abundance to examine how historic grazing (a legacy effect of grazing due to different land tenures) and current grazing intensity (grazing over the last 5-10 years) affected biotic community composition in a semi-arid woodland. Ants are a useful organism with which to examine disturbance effects because they play important roles in belowground and detritivore systems (Shik & Kaspari 2010) and are critical to a wide range of ecosystem functions such as seed dispersal, and decomposition. They are also ubiquitous and easily sampled (Hoffmann 2010). Several Australian and global studies (e.g. Hoffmann

2000, 2010; Nash et al. 2001; Bestelmeyer & Weins 2001) have revealed mixed effects of grazing on ant communities, with inconsistent effects of increasing grazing pressure on ant richness (Hoffmann 2000; Nash et al. 2004), but substantial effects on community composition (Bestelmeyer et al. 1996; Claver et al. 2014). Studies typically indicate that disturbance by grazing generally increases thermophilic species that are better adapted to open, often disturbed environments (Hoffmann and Andersen 2003;

Claver et al. 2014), suggesting that grazing leads to alterations in community structure

(Eldridge 2016).

Responses of ants to changes in environmental condition are likely to be less pronounced for those species that spend most of their time below ground. Many ant species live subterranean lifestyles; nesting, foraging, and inhabiting belowground ecosystems sometimes exclusively (Wilkie et al. 2007; Andersen & Brault 2010;

Masuko 2010). Belowground ant communities have been rarely studied, and little is known about how they are influenced by aboveground disturbances such as grazing.

Given the close links between above- and belowground processes, it is reasonable to

92 predict that changes in aboveground structures resulting from grazing would have flow-on effects to belowground communities.

Herein we report on a study that aims to test the effects of historic and current grazing on above- and below-ground ant communities in a semi-arid woodland. We used sites that differed in grazing history, and current grazing (grazing intensity), using distance to water as a proxy for current grazing. We had three predictions. First, we expected that ant richness would be relatively consistent across grazing histories, but that community composition would change to benefit those species that prefer simplified habitats that typically result from high levels of current or historic grazing intensity.

Second, we expected that ant species richness would follow a logistic relationship along the gradient in current grazing intensity, consistent with predictions under the piosphere model (e.g. Graetz & Ludwig 1978). Finally, we predicted that above- and belowground ant communities would show similar responses to increasing grazing- induced disturbance because above- and below-ground processes have been shown to be closely interrelated (Wardle et al. 2004).

5.3 Methods

5.3.1 The study area

The study was undertaken in woodland dominated by white cypress pine (Callitris glaucophylla Thompson & Johnson) in and around the township of Goolgowi in south- eastern Australia (-33.815, 145.637). The landscape is dominated by level to slightly

93 undulating plains of Quaternary alluvium and colluvium, supporting red earth soils with loam to clay loam surface textures. The climate is Mediterranean, with about 20% more rain falling during the six cooler months. Mean annual rainfall is about 370 mm, and average temperature ranges from 11°C in winter (July) to 25°C in summer

(January). Other common trees within these woodlands include Eucalyptus spp. and

Allocasuarina luehmannii (Baker) Johnson, with understorey often being open, with sparse Acacia spp., Hakea spp., and Dodonaea spp. shrubs.

The study was conducted at nine sites within conservation reserves, commercial

Callitris forests, private land, and road reserves. The nine sites comprised three levels of historic grazing each with three replicates, based on land tenure, grazing history and the time since the cessation of livestock grazing. Sites that were long ungrazed by livestock (hereafter ‘long ungrazed’) were selected from reserves around small towns and travelling stock routes, roadside reserves along which livestock are moved in drought years. Long ungrazed sites had a history of relatively infrequent grazing by livestock over the past 35 years, as livestock are now almost exclusively transported to markets by road transport rather than being herded along these road reserves by stockmen. Three sites were selected where livestock had been removed in the three years prior to field surveys (hereafter ‘recently ungrazed’). These sites were known to support variable levels of livestock grazing at rates limited by state government authorities. Currently grazed sites (hereafter ‘currently grazed’) had more sustained levels of historic grazing, based on set stocking (livestock retained in the paddock year- round). Stocking rates here would have been greater than recently ungrazed sites because they are on private land where grazing rates are largely uncontrolled. At the

94 time of our surveys, all sites were grazed by kangaroos (Macropus spp.) at relatively low densities (1-5 animals km2). These three categories of time since grazing correspond closely to differences in landscape condition, based on the cover of bare soil and erosion. They also corresponded to measures of the mass of livestock dung and the density of livestock tracks (Appendix C).

At each of the nine sites we selected seven positions along a gradient with increasing distances from water. This gradient acted as a proxy of recent grazing pressure, with sites close to water currently heavily grazed compared with those at a long distance from water. The effects of grazing were therefore consistent with the piosphere effect, which describes changes in biotic and abiotic attributes with distance from the water source (Lange 1969; Graetz & Ludwig 1978; Hoffmann 2000). Piospheres are often used as a surrogate of changing grazing intensity, and have been used to examine the effects of grazing on ant communities (Hoffman 2000). We established a 1 km transect, starting at a water point, along which we sampled ants at 25 m, 50 m, 100 m, 200 m,

500 m, 750 m and 1000 m from the edge of the water point. Due to the relatively small size of the paddocks (< 9 km2) and the placement of more than one water point per paddock, 1000 m was generally the maximum distance we could find from any water point.

5.3.2 Ant and ground cover sampling

Five aboveground and five belowground pitfall traps were placed at each of the seven positions from water. Belowground traps were established in parallel lines about 20 m long (hereafter ‘trap lines’) about 20 m from aboveground traps, and equidistant from the watering point. Aboveground pitfall traps (polypropylene cups, 6.4 cm diameter, 95 7.6 cm deep) were placed flush with the soil surface, and 30 ml of propylene glycol added. Propylene glycol was used as the pitfall killing agent for ants, as it has been proven to be non-toxic to vertebrates (Bestelmeyer et al. 2000). Belowground traps

(50 ml polypropylene centrifuge tubes, 4 cm diameter, 10 cm long) were baited with an equal mixture of tuna, peanut butter and honey applied to the lid of the tubes above four holes drilled near the top. Belowground traps were then filled with 30 ml of propylene glycol, and buried 20 cm below the soil. Aboveground and belowground traps were left to collect ants for two weeks in February 2014.

Collected ants were transferred to 70% ethanol for storage and identification. Ants were identified to species and morphospecies using appropriate keys (Andersen 2000;

Shattuck 2000; Heterick 2001, 2009; Heterick & Shattuck 2011; McArthur 2007, 2014) and comparison with museum specimens. Voucher specimens of each species were deposited in the Australian Museum collection. Ants were assigned to a functional group following Andersen’s (1995) classifications.

Along each 20m line in which pitfall traps were placed we sampled five 1m2 quadrat at evenly spaced intervals. Within each quadrat we recorded percent coverage of leaf litter, biocrusts (cyanobacteria, algae, mosses, liverworts, fungi, bacteria and lichens ), ground-plants, and open ground. Ground cover from all five quadrats were then averaged to get the average cover at each position from water (25 m, 50 m, 100 m,

200 m, 500 m, 750 m and 1000 m).

96 5.3.3 Statistical methods

We used generalized linear models with a Poisson error structure to calculate species and functional group richness. Distance from water was standardised by subtracting the mean from each distance value and dividing by the standard deviation. Analyses were conducted with the R package lme4 (Bates et al. 2014) and post-hoc Tukey’s analysis with R package multcomp (Hothorn et al. 2016). Models were structured with the grazing history, grazing intensity, and their interaction as fixed effects, with site nested within grazing history included as random intercepts.

Variation in ant species composition among grazing history and distance categories was explored using non-metric multidimensional scaling and the Bray-Curtis similarity matrix using species presence/absence data with the PERMANOVA package (Anderson et al. 2008). Where significant differences in species composition were identified in relation to either grazing history or grazing intensity, we used multi-level indicator species analysis (R package: indicspecies; De Caceres & Jansen 2016) to test the strength of association between individual ant species and grazing history or intensity.

The indicator value is maximal (IV = 1) when all individuals of a given species are restricted to a treatment, and when all samples from a particular treatment contain an occurrence of that species.

We used Structural Equation Modelling (SEM) to explore relationships among grazing history, i.e. time since grazing (currently grazed = -1, recently ungrazed = 0; long ungrazed = +1), grazing intensity (distance from water) and ant richness and the potential mediating effects of the cover of bare soil, groundstorey plants, litter and 97 biocrust. Separate models were constructed for aboveground and belowground ants, and the Dominant Dolichoderinae, Generalized Myrmicinae, Hot Climate Specialists,

Opportunists and Subordinate Camponotini. Structural equation modelling tests the plausibility of a causal model, based on a priori information, in explaining the relationships among different variables. In our model, we predicted that grazing intensity and grazing history would have direct and indirect effects on richness of aboveground communities (Appendix D). Given that they would forage aboveground and be influenced by habitat features that control their foraging ability (e.g. Gibb and

Parr 2010). Structural equation modelling allowed us to partition direct and indirect effects of one variable upon another and to estimate the strengths of these multiple effects. This is particularly important in grazing studies because grazing was expected to have indirect effects on ant community composition by changing soil surface configuration and therefore altering foraging efficiency.

To normalize the data, cover values were standardized (z-transformed) prior to analyses. Overall goodness of fit probability tests were performed to determine the absolute fit of the best models. The goodness of fit test estimates the long-term probability of the observed data given the a priori model structure. Thus, high probability values indicate that these models are highly plausible causal structures underlying the observed correlations. The models with the strongest measures of fit

(e.g. low χ2) were interpreted as showing the best fit to our data. All SEM and pathway analysis was conducted using AMOS Software Version 20. The stability of these models was evaluated as described in Reisner et al. (2013).

98 5.4 Results

5.4.1 Ant species richness

We trapped a total of 340,928 ants, with five-times more ants from belowground traps

(84% of total abundance) than aboveground traps. A total of 112 ant species were sampled, from 33 genera, and five subfamilies (Appendix E). Although belowground traps sampled a greater abundance of ants, belowground richness (56 species) was lower than aboveground (103 species). Ninety-six species were unique to aboveground communities and nine to belowground communities (Appendix E). Of the unique belowground species, Solenopsis clarki was found at every site on every trap line, but never in aboveground traps. Similarly, Solenopsis belisaurius was found at every site in belowground traps but never in aboveground sampling. Common genera sampled in above- and belowground traps were Camponotus (Formicinae) with 15 species,

Melophorus (Formicinae) and Monomorium (Myrmicinae) with 13 species each, and

Iridomyrmex (Dolichoderinae) with 11 species (Appendix E).

For aboveground ant communities, species richness was lowest at long ungrazed sites and greatest at currently grazed sites (0.093 ± 0.043; estimate ± SE, P = 0.035; Fig.

5.1A). There were no differences, however, for belowground species richness (P =

0.369; Fig. 5.1B). There were no significant differences in aboveground (P = 0.155) or belowground (P = 0.504) ant species richness in relation to grazing intensity (Fig. 5.2) and no significant grazing history by current grazing intensity interactions (Appendix F).

99

Figure 5.1 Ant species richness in relation to three levels of historic livestock grazing for aboveground and belowground ant communities. For aboveground ants, different letters indicate a significant difference among grazing levels for above-ground species at P < 0.05. There were no significant differences for belowground ant communities.

Currently grazed sites had greater species richness of Hot Climate Specialists (0.20 ±

0.073, P = 0.006) and subordinate Camponotini (0.231 ± 0.079, P = 0.003; Appendix F).

Increasing grazing intensity reduced the richness of Dominant Dolichoderinae (-0.176 ±

0.065, P = 0.007; Fig. 5.3) and Hot Climate Specialists (-0.133 ± 0.058, P = 0.021l; Fig.

5.3). There were no significant interactions between grazing history and grazing intensity for any functional groups (Appendix F).

100

Figure 5.2 Comparison of above and below ground ant species richness with distance from water. Fig. A represents changes in mean species richness in three different grazing histories (long ungrazed, recently ungrazed, currently grazed) along a decreasing grazing intensity gradient (declining with increased distance). Fig. B shows average (± 95% CI) change of aboveground and belowground ant species richness between all samples in relation to increasing distance from water (declining grazing intensity). There were no significance between richness and grazing intensity (P > 0.05, Appendix F).

101

Figure 5.3 Mean (± 95% CI) species richness of the five most speciose ant functional groups with increasing distance from water, summed over above-ground richness. Models for the Dominant Dolichoderinae and Hot Climate Specialists were significant for diversity change with distance from water (P < 0.05; Appendix F).

5.4.2 Ant community composition

Grazing history (PERMANOVA: F (perm) = 2.53, P (perm) = 0.014) and current intensity

(PERMANOVA F (perm) = 1.43, P (perm) = 0.010) were significant predictors of

102 aboveground ant community composition. Intensity effects were consistent among the three levels of grazing history and there was a clear separation among the three grazing history classes (t (perm) < 0.07; Appendix G). For current grazing intensity, pairwise tests indicated a significant difference between the closest (highest intensity;

25 m and 50 m) and most distant (lowest intensity; 1000 m) sites in relation to the waterpoint (t (perm) = 0.04).

Eleven ant species, principally Hot Climate Specialists (Melophorus and Meranoplus species) were significant indicators of historically high levels of grazing. For belowground communities, however, only five species, mainly Hot Climate Specialists, were significant indicators of grazing history (Table 5.1).

103

Table 5.1 Ant species indicative of different grazing histories (time since grazing) for aboveground and belowground samples. Functional groups based on Andersen (1995). Indicator ant species Functional Grazing Indicator P- group# history value value Aboveground taxa Melophorus cf. pallipes Hot Currently grazed 0.58 0.001 Iridomyrmex calvus Dominant Currently grazed 0.45 0.004 Monomorium sp. 1 Generalized Currently grazed 0.44 0.007 Camponotus ephippium Subordinate Currently grazed 0.40 0.009 Camponotus sp. 13 Subordinate Currently grazed 0.40 0.009 Camponotus sp. 5 Subordinate Currently grazed 0.37 0.040 Melophorus cf. bagoti Hot Currently grazed 0.37 0.031 Melophorus cf. group H Hot Currently grazed 0.34 0.044 Melophorus cf. anderseni Hot Currently grazed 0.34 0.039 Meranoplus sp. 1 Hot Currently grazed 0.33 0.035 Camponotus cf. loweryi Hot Currently grazed 0.32 0.025 Iridomyrmex cf. macrops Dominant Recently ungrazed 0.43 0.009 Meranoplus sp. 4 Dominant Recently ungrazed 0.37 0.029 Iridomyrmex sp. 8 Hot Recently ungrazed 0.37 0.019 Doleromyrma darwiniana Opportunist Long ungrazed 0.54 0.023 Belowground taxa Iridomyrmex cf. brunneus Dominant Currently grazed 0.51 0.001 Melophorus fieldi Hot Currently grazed 0.34 0.023 Monomorium sp. 12 Generalized Recently ungrazed 0.37 0.028 Melophorus aeneovirens Hot Long ungrazed 0.34 0.045 Melophorus cf. turneri Hot Long ungrazed 0.34 0.040

104

Table 5.2 SEM coefficients for the relationships between grazing history (time since grazing) and intensity (distance from water), bare soil cover, plant cover and litter cover and total aboveground and belowground ant richness and richness of five functional groups. Only significant SEM coefficients are shown. Attribute Grazing Grazing Bare Biocrust Litter Plant Model history intensity soil cover cover cover R2 Aboveground richness -0.38 -0.27 0.38 0.33 0.21 Belowground richness 0.04 Dominant Dolichoderinae -0.43 -0.39 0.25 Generalized Myrmicinae -0.22 0.16 Hot Climate Specialists -0.33 -0.34 0.26 Opportunists 0.39 0.16 Subordinate Camponotini -0.50 -0.27 0.40 0.43 0.24 0.26 Bare soil -0.35 Biocrust cover 0.65 -0.28 Litter cover -0.22 Plant cover 0.44 0.20

5.4.3 Grazing and environmental effects on ant species richness

Our structural equation models indicated strong direct and suppressive effects of time since grazing on richness of aboveground ants, and relatively strong indirect effects mediated by changes in litter cover (Fig. 5.4A; Table 5.2). Increased grazing intensity reduced the positive effect of biocrust cover on ants, and increasing time since grazing suppressed the positive effect of litter cover on ants (Fig. 5.4A; Table 5.2). There were no effects of grazing on belowground ant species richness (Fig. 5.4B; Table 5.2).

For individual functional groups, increasing time since grazing was associated with reduced richness of Dominant Dolichoderinae, Hot Climate Specialists and Subordinate

Camponotini, no effect on Generalized Myrmicinae, and increases in Opportunists

105 (Table 5.2). The effects of increasing grazing intensity were generally a reduction in richness of all functional groups with increasing distance from water, except

Opportunists, which did not change. Higher species richness of Subordinate

Camponotini was associated with greater cover of plants, litter and biocrusts (Table

5.2).

106

Figure 5.4 Structural equation models for (A) aboveground and (B) belowground ant species richness in relation to time since grazing (grazing history) and intensity (distance from water) and the cover of biocrusts, litter, bare soil and plants. Histograms indicate the standardised total effects (STEs) for the six attributes. Standardized path coefficients, embedded within the arrows, are analogous to partial correlation coefficients, and indicate the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. The proportion of variance explained (R2) is shown for each attribute. Only significant pathways are shown in the models. Model fit: χ2 = 2.19, df = 4, P = 0.701. History = historic grazing (time since grazing), Intensity = grazing intensity (distance from water).

107

5.5 Discussion

We found very few effects of grazing history or intensity on belowground ants, but marked changes in the composition of the aboveground ant community, particularly in relation to grazing history. Our grazing gradient approach revealed that, unlike predicted responses for plants and some fauna, most changes in aboveground ants occurred within 100 m of the livestock watering points, with subtle and idiosyncratic effects at distances of up to 1 km from water. Our structural equation modelling showed that biocrust cover and litter cover were the strongest predictors of aboveground ant richness but were unrelated to richness of belowground ants.

Furthermore, aboveground richness declined with increasing time since grazing (i.e. reduced historic grazing) and with increasing intensity of grazing (distance to water).

Overall, our results suggest that both grazing history and grazing intensity have similar effects on aboveground ant community structure at least for relatively small paddocks with short gradients in grazing intensity.

5.5.1 Grazing effects on ant community structure

Historic and current grazing intensity had similar effects on ant community composition. The standardised total effects (i.e. the sum of direct and indirect effects) of grazing history and current grazing intensity for aboveground ants were both negative and of a similar magnitude, and both had opposite effects on composition to soil surface features, particularly biocrust and litter cover. For belowground ants, however, there were no effects of either environmental variables or our two measures

108 of livestock grazing. Richness of both Hot Climate Specialists and Subordinate

Camponotini was greater at currently grazed than long ungrazed sites, and Hot Climate

Specialists comprised a greater proportion of taxa that are indicative of currently grazed sites. Currently grazed sites had the greatest species richness and long ungrazed sites the least, consistent with studies of ant (Hoffmann 2000, 2010; Nash et al. 2001; Pere et al. 2010), invertebrate (Lindsay and Cunningham 2009), vertebrate

(Taylor 1986), and plant (Eldridge et al. 2011) community responses to landscape condition worldwide. However, many studies have failed to show effects of grazing- induced disturbance on ant species richness (Read & Andersen 2000 Claver et al.

2014). Part of the reason for these idiosyncratic results may relate to the fact that livestock do not have a direct trophic effect on ants. Rather, livestock alter ant community structure indirectly by changing food supply, habitat structure, and species interactions (Andersen 1995; Hoffmann 2010). Variables such as soil type (Bestelmeyer et al. 2006), plant community (Bestelmeyer & Wiens 2001), and landscape structure

(Pere et al. 2010) are important factors influencing ant communities, and can vary in how disturbance affects them.

Concurrent studies at our woodland sites indicate that livestock grazing simplifies ecosystem structure by reducing plant, litter, and biocrust cover, altering plant community composition, and reducing the size distribution of perennial grass tussocks

(Eldridge et al. 2013; Eldridge et al. 2016). In higher rainfall woodlands, changes in grass tussock density have been shown to have a greater influence on ant richness and abundance than increases in grazing intensity (Barton et al. 2016), though these impacts likely vary among functional groups. Woodlands could provide refugia for

109 arboreal species that are less susceptible to grazing-induced changes in groundstorey vegetation because of their reliance on woody plants (Hoffmann & Andersen 2003;

Lindsay & Cunningham 2009).

Contrary to our second hypothesis, the data did not conform to trends consistent with the piosphere effect, which describes logistic biotic and abiotic responses to degradation around livestock watering points (Lange 1969). These effects, which have been demonstrated in plants, soil chemistry and soil surface integrity (e.g. Andrew and

Lange 1986) are strongly pronounced close to water, but attenuate in a logistic fashion with increasing distance from water (Graetz & Ludwig 1978). Studies of ants along grazing gradients radiating from watering points typically indicate less richness under very high intensity grazing, generally close to water, and slight increases with greater distances from water (Hoffmann 2000; Nash et al. 2004; Hoffmann & James 2011).

However, discontinuities in piosphere effects are common (Friedel 1997), and may occur due to differences in geomorphology, fencing, natural obstructions such as drainage lines, and often the size of the sacrifice zone, i.e. the area of severe grazing- induced degradation around water (Sasaki et al. 2008). We found that changes in richness of aboveground ants were most marked within this ‘sacrifice zone’, with richness increasing and peaking within 100 m from water (Fig. 2). Beyond 100 m from water, ant species richness was relatively constant, with distance from water, particularly for the composition of Generalized Myrmicinae and Hot Climate Specialist functional groups. Our results show that this did not vary with grazing history i.e. the zone of maximum richness was found consistently at about 100 m, irrespective of whether sites had been long ungrazed or were currently grazed. This suggests to us

110 either a strong legacy effect from previous grazing, in the case of sites long ungrazed for over 35 years, or an ant response that is focused on proximity to water, irrespective of landscape condition. It is also possible that a critical threshold of grazing intensity by free-ranging or native herbivores, such as feral goats and kangaroos, may exist around this position from water at all sites. The trend in richness that we observed out from water was more consistent with predictions under the Mass Ratio

Hypothesis (Grime 1998) whereby richness peaks at sites of frequent, high intensity disturbance (Kershaw & Malik 2013), similar to observations of compositional change in plants (Sasaki et al. 2008) and ants (Hoffmann 2000) in similar arid and semi-arid environments.

The lack of concordance with a logistic response suggests to us that the ant community at our sites are relatively resistant to grazing (sensu Sasaki et al. 2008). It may also relate to the relatively small paddock sizes in our study, with livestock able to access all parts of the paddock during most years; hence there was a weak distance effect.

Nevertheless, we did detect some changes in individual functional groups, with richness of Dominant Dolichoderines and Hot Climate Specialists declining, and

Opportunists increasing, with increasing current grazing intensity. Opportunists are able to exploit resources in more disturbed environments (Andersen 1995; Hoffmann

2000; Hoffmann and Andersen 2003) whereas Dominant Dolichoderinae and Hot

Climate Specialists favour more stable environments with lower disturbance (King et al. 1998; Hoffmann and Andersen 2003). Opportunist genera such as Rhytidoponera and Tapinoma are able to exploit more resource-poor environments such as the highly-disturbed sacrifice zones around water where they can avoid direct competition

111 with Dominant Dolichoderinae or Hot Climate specialists. The latter two functional groups require more stable environments and resources for their colonies to gain a competitive advantage over other groups that can exploit resource-poor environments

(Andersen 1995; King et al. 1998). Niche segregation by different species in the

Dominant Dolichoderinae (e.g. Iridomyrmex spp.) and Hot Climate Specialist (e.g.

Melophorus spp.) functional groups allows ants to avoid competition and therefore coexist by adjusting their foraging times to different times of the day (Andersen 1995;

Hoffmann & Andersen 2003).

5.5.2 Drivers of ant community structure

Ants have been used widely to assess changes in environmental conditions brought about by changes in human-induced land use (Nash et al 2001; Hoffmann & Andersen

2003; Gomez & Abril 2011), regional climates (Folgarait 1998; Segev 2010) and natural disturbances (Verble & Yanoviak 2013; Glasier et al. 2015). The results of our structural equation modelling provide some insights into the effects of grazing and associated shifts in environmental condition on the richness of the entire ant community and specific functional groups. For aboveground ants, both grazing history and intensity suppressed the positive effect of biocrust cover on aboveground ant richness. Grazing history, however, had a slight indirect stimulatory effect on aboveground ant richness by enhancing litter cover. Increasing time since grazing and increasing grazing intensity were associated with declines in all functional groups, except Opportunists, which increased with increasing time since grazing (Table 2). Livestock herbivory and trampling increases litter cover by detaching plant material (Zimmerman &

112 Neuenschwander 1984) and livestock grazing has been shown to increase the scattering of litter (Daryanto et al. 2013). Litter cover provides an important habitat for ants by moderating soil surface temperatures, providing substrate for potential prey and refugia against predators (Shik & Kaspari 2010). Biocrust cover may enhance ant richness via a number of mechanisms. For example, the presence of biocrusts might increase the foraging efficiency of ants during the hotter times of the day by moderating soil surface temperatures (Escolar et al. 2015). Crusts might also provide a more stable environment for ant movement due to their soil stabilising abilities (Li et al. 2010). We did detect general positive effects of plant, litter and biocrust cover on the richness of Subordinate Camponotini, but no effects on other ant functional g roups

(Table 2). As Subordinate Camponotini are associated with more stable environments

(Hoffmann and Andersen 2003), changes in ground cover may be important in determining the number of species able to use disturbed environments.

Of particular interest in our study is the fact that we did not detect any effects of grazing, historic or current intensity, or any environmental variables on the richness of belowground ants or any belowground functional groups. There are few global studies of belowground ant communities, though see Wilkie et al. (2007), Andersen and Brault

(2010) and Masuko (2010). The effect of disturbance on belowground ant communities is even less well known. Our results indicate that aboveground disturbances such as livestock grazing, and changes in surface environments such as ground cover have little effect on belowground ant communities in a semi-arid woodland community. This suggests that belowground ant communities are not only resistant to surface

113 disturbances, but that there is niche segregation with aboveground species, through exploitation of resources not used by aboveground ants.

5.5.3 Concluding remarks

Grazing history and current grazing intensity had similar suppressive effects on aboveground ant communities but no effects on belowground ants. An increase in aboveground ant species richness and change in community composition in currently grazed areas, primarily through an increase in Hot Climate Specialists, is consistent with habitat simplification and increased temperatures within grazed woodlands. This simplification indicates that grazing has a legacy effect on semi-arid woodlands with marked changes in aboveground ant community structure. These changes can have wide ranging ecosystem effects given the role played by ants as ecosystem engineers and their effect on many ecosystem functions (Folgarait 1998). Belowground ant communities in our study were largely resistant to grazing disturbance, suggesting strong niche segregation compared with aboveground species, though more research is needed to test this. Finally, our results show that belowground ant communities are resistant to disturbances on the soil surface that would normally be associated with overgrazing, i.e. reductions in soil cover and quality. This has important implications for how ant community composition is used as a bioindicator of ecosystem health in woodlands in relation to grazing.

Publication details: Glasier James R.N., Eldridge David J. (in review). Variable effects of current and historic livestock grazing on above- and below- ground ant communities in a wooded dryland. Ecosystems.

114 Chapter 6

Conclusion: Ecology of ant and myrmecophile

6.1 General Discussion

The objective of my thesis was to examine the ecological importance of ants and their interactions. To facilitate this, in Chapter 1, I presented a simple conceptual model using ants as the focal taxa, with predictive interactions between ants, myrmecophiles, the environment, and disturbance (Fig. 1.1). I then tested the different pathways of this model to determine the effects that they had on ants and/or myrmecophiles. The use of ants as a focal taxon allowed me to test global and more localized questions, expanding our knowledge of both ants and myrmecophiles. My findings contribute to the knowledge of myrmecophile biodiversity, associations, and overall ant ecology.

My research focused on three main pathways. The first pathway was how the environment and ant species richness influenced richness of myrmecophiles at a global level (Chapter 2). The second pathway I tested was the interactions between ants and myrmecophiles (Chapter 3 and 4). The third pathway, examined was the influence of disturbance on above and below-ground ant communities, necessarily including the influence of disturbance on the environment (Chapter 5). The results from my thesis are globally relevant to understanding symbiotic associations, ant influences on myrmecophile diversity, and understanding what types of disturbances may influence ant diversity.

In Chapter 2, I tested the model pathways between the environment, ants, and myrmecophiles. More specifically, I examined how global environmental patterns and

115 ant species richness influenced myrmecophile species richness. By using ants as a common host with a global distribution, I could further test and quantifiably compare how a spectrum of symbiotic relationships were distributed across the globe. Overall global myrmecophile diversity patterns mirrored ant diversity patterns, becoming richer towards the equator (Dunn et al. 2009). However, myrmecophile relationship types showed differing patterns. Both mutualist and parasitic myrmecophiles did not follow the common latitudinal trends, while commensals and kleptoparasites did.

Moreover, only commensals were positively correlated with ant species richness, while the other three relationship types were correlated with environmental variables

(Chapter 2). The implications of these results are that environmental variables drive myrmecophile relationship types, and that myrmecophile diversity is not just a function of ant diversity. For mutualist myrmecophiles, which often feed on plants, net primary productivity was a major driver of species richness, indicating that host plants may also play a role in their richness. Commensalisms have rarely been studied on a global scale, and my findings indicate that host richness drives symbiont richness.

Kleptoparasites require higher availability, reliability, and stability of food resources from a host (Iyengar 2008); and my findings of areas of dry, low variation in annual temperature and high net primary productivity further supports this (Chapter 2). For parasitic myrmecophiles, patterns of seasonality were found to be major drivers of species richness a result similar too other parasitic groups. Seasonality has been suggested to allow parasites to exploit hosts at reliable times of year, driving higher parasite diversity in temperate regions (Wcislo 1987). The findings in Chapter 2 indicate that the evolution of symbiotic relationships is influenced not only by a host, but also by the effects the environment has on resource availability and stability.

116 Associations between ants and myrmecophiles are diverse and wide ranging (Kistner

1982). In Chapter 3, I tested the model pathway between ants and myrmecophiles, to see how ant traits influenced myrmecophile richness per ant species. Determining how host traits effect species richness and symbiotic relationships of myrmecophiles, is integral to understanding the ecology of these associations. My research further expanded on previous work that found that colony-size was an important variable in myrmecophile diversity (Päivinen et al. 2003). Ant species with large colonies have higher myrmecophile richness than ants with smaller colonies. Larger colonies provide more resources, more opportunity to interact with an ant, and more habitat space (in the form of larger nests). However, additional traits such as number of spines and stings also influenced myrmecophile richness per ant, implying that there are important evolutionary advantages to associating with certain morphological traits

(Chapter 3). As we are still learning about how traits, such as spines, function in ants

(Dornhaus and Powell 2010; Blanchard and Moreau 2016), this may imply that myrmecophiles could be playing an important role in the morphological evolution of ant species. Additionally, if the morphological traits, such as spines, are indeed defence against predation (Ito et al. 2016), our findings indicate that mutualist and commensal myrmecophiles may benefit from these protections.

In Chapter 4, I again tested the ant-myrmecophile pathway of my model, seeking to determine how the type of symbiotic relationship influences host range of myrmecophiles. Host range is an important part of symbiont life-history as a higher host-breadth allows for easier discovery of a host, while narrow host breadth often allows for stronger symbiotic associations (Thompson 1994). As ants have highly

117 guarded social societies, most myrmecophiles exhibit narrow host ranges to better exploit the resources associated with those societies. However, we found that detrimental relationships had narrower host-breadth, compared to beneficial myrmecophiles (Chapter 4). These findings indicate that there are great evolutionary pressures limiting host range of detrimental myrmecophiles.

In Chapter 5, I further tested the disturbance, environment, and ant pathways of my model, at a local scale. Disturbance is an integral part of ecology, driving ecosystem structure and diversity. Ant communities are no exception, being influenced by both frequency and intensity of disturbances (Hoffman 2010). However, it is common for less drastic disturbances, such as grazing, to have a limited effect on ant diversity, instead changing only community structure. For below-ground ant communities, little has been studied on how disturbance changes these communities (Wong and Guenard

2017). I found that grazing history and intensity reduced habitat structure (decrease in biocrust, vegetation, and litter cover), it had no effects on belowground ant species richness or community structure. The lack of effects on below-ground ant communities by grazing indicate subterranean ants are resilient, even resistant, to grazing disturbance. The implications of these findings are that below-ground ant communities within the semi-arid region of eastern Australia, may not be influenced greatly by above-ground ecology, but by yet unknown variables. For above-ground ant communities however, grazing did have an impact. Changes within the environment indicated a simplified habitat, with more open ground, less vegetation, and reduced biocrust cover in grazed areas. This simplified structure caused by grazing, was also reflected by the changes within that ant community, with ants that favour these

118 environments, such as hot climate specialists increasing with grazing. Overall grazing disturbance had strong suppressive effects on aboveground ant richness and a simplification of the local environment.

6.2 Future Directions

Although I presented a simple conceptual model at the beginning of my thesis, it provides additional pathways by which we can use ants as focal taxa for future research. Moreover, research of already tested pathways, using additional methods would help clarify or add to my findings. For example, although we used a global database and found comprehensive patterns of myrmecophile richness, more direct experimental research would be beneficial. Directly sampling myrmecophile richness patterns across a large latitudinal gradient, and recording in-depth environmental variables may improve our understanding of why different myrmecophile relationships show different richness trends. Additionally, directly sampling myrmecophiles and recording their relationships with ants through additional observation or even manipulative experiments, would help to eliminate any literature bias that can occur from data syntheses. Moreover, directly sampling myrmecophiles and their ant hosts in regions like Africa and Asia, where sampling has been low (Chapter 2), would greatly increase the not only our knowledge of those organisms but a more equal examination of myrmecophiles.

The relationships among hosts and symbionts can be complex, and this is true for associations between ants and myrmecophiles (Parker 2016). My finding of a lack of ant traits driving parasitic myrmecophile species richness per ant species implies that

119 we know very little about these associations and that more research is needed. Several potential avenues could be explored, particularly on chemical communication.

Myrmecophiles that need to infiltrate an ant colony must be able to ‘trick’ an ant into accepting it, either through tactile (Hölldobler 1971), audio (Sala et al. 2014), and/or chemical cues (Akino 2002; Edgar & Allan, 2006). Research focusing on these cues, particularly chemical cues, a primary method in ant communication (Hölldobler, 1971), may be needed to help explain why some ants have more parasites than others.

Research into ant cuticular hydrocarbons has been informative not only for ant sociality, but for ant-myrmecophile interactions (Howard et al. 1990). Many myrmecophiles use cuticular hydrocarbons to trick their hosts, and it maybe that different hydrocarbon traits may deter parasites (Howard et al. 1990; Edgar & Allan

2006). Additionally, looking at traits such as antennal sensitivity may allow us to determine more readily myrmecophile richness per ant species.

Ant morphology played an important part in traits that influenced myrmecophile richness per species. However, understanding why traits, such as number of spines, impacts myrmecophile richness of an ant species needs to be examined more closely.

Spines and stings have both been described as defensive traits (Blanchard & Moreau

2016), but it is still unknown how many morphological traits help in defence (Dornhaus and Powell 2010). Direct observations of traits and conflict between ants, ant predators, and with myrmecophiles are needed.

Below-ground ant communities are rarely studied, and are only recently being recognized as being important parts of the ecosystem (Wong and Guenard 2017).

120 Future study using standard sampling techniques, will be important to better compare results between studies (Wong and Guenard 2017). Additionally, studying what subterranean ant species are doing, how they interact with the above-ground ecosystem, and examining their life-history, will be an important for better understanding ant ecology across the globe.

An additional, but untested pathway from my conceptual model was disturbance effects on myrmecophiles. Disturbance can have direct effects on ant communities and individual ant colonies (Hoffman 2010; Chapter 5). Consequently, one would expect changes within an ant colony to have a direct effect on a myrmecophile, and changes within a community to have changes on myrmecophile diversity. Testing association rate before and after disturbances, examining how stresses on a colony change the abundance or richness of myrmecophiles, and determining the stress thresholds that colonies are able to withstand to support a myrmecophile community are all important research questions that need to be addressed in the future.

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140 Appendix A

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165 Appendix C

Mean attributes of sites with different grazing histories.

Attribute Currently Recently Long grazed ungrazed ungrazed Erosion cover % 22a 12ab 2b Bare soil cover (%) 17 9 0 Native plant cover (%) 45a 44a 39b Exotic plant cover (%) 4 10 1 Plant cover (%) 42a 65b 23a Biocrust cover (%) 19a 9c 36b Litter cover (%) 21 17 31 Grass density (plants m-2) 9.5 14.0 2.7 Livestock dung (kg ha-1) 33 27 16 Livestock tracks (m ha-1) 105 29 0

These attributes were assessed previously by Eldridge and the Arid Ecology Lab, UNSW.

166

Appendix D

Appendix D. A priori structural equation model on how grazing disturbance effects ant species richness.

167 Appendix E

Appendix E. Abundance of ants sampled from above- and belowground traps, their subfamily, and functional group (after Andersen 1993).

Subfamily Species Functional Aboveground Belowground Group Dolichoderinae Arnoldius flavus Cryptic 0 430 Dolichoderinae Doleromyrna darwiniana Opportunist 120 9122 Dolichoderinae Dolichoderus omicron Cold 11 0 Dolichoderinae Froggattella kirbii Dominant 55 0 Dolichoderinae Iridomyrmex calvus Dominant 21014 22492 Dolichoderinae Iridomyrmex sp 2 Dominant 288 0 Dolichoderinae Iridomyrmex sp 3 Dominant 107 0 Dolichoderinae Iridomyrmex purpureus Dominant 959 1 Dolichoderinae Iridomyrmex brunneus Dominant 1533 10863 Dolichoderinae Iridomyrmex sp 6 Dominant 344 1973 Dolichoderinae Iridomyrmex sp 7 Dominant 177 2277 Dolichoderinae Iridomyrmex sp 8 Dominant 13863 241 Dolichoderinae Iridomyrmex sp 10 Dominant 1 32 Dolichoderinae Iridomyrmex minor Dominant 42 800 Dolichoderinae Iridomyrmex macrops Dominant 81 0 Dolichoderinae Ochetellus glaber Opportunist 3 0 Dolichoderinae Tapinoma cf. minutum Opportunist 871 80 Dorylinae Lioponera c.f. fervida Specialist 41 1000 Dorylinae Ooceraea australis Specialist 5 40853 Dorylinae Lioponera c.f. Specialist 6 1 inconspicua Dorylinae Lioponera c.f. brevis Specialist 1 11 Dorylinae Lioponera c.f. clarki Specialist 38 0 Dorylinae Lioponera c.f. clarus Specialist 3 0 Formicinae Camponotus cf. loweryi Subordinate 486 1 Formicinae Camponotus ephippium Subordinate 310 0 Formicinae Camponotus sp 1 Subordinate 73 0 Formicinae Camponotus sp 2 Subordinate 82 0 Formicinae Camponotus sp 3 Subordinate 19 0 Formicinae Camponotus sp 4 Subordinate 4 0 Formicinae Camponotus sp 5 Subordinate 12 0 Formicinae Camponotus sp 6 Subordinate 2 0 Formicinae Camponotus sp 7 Subordinate 13 0 Formicinae Camponotus sp 8 Subordinate 311 0 Formicinae Camponotus sp 12 Subordinate 1 0 Formicinae Camponotus sp 14 Subordinate 2 0 Formicinae Camponotus sp 15 Subordinate 1 0 Formicinae Camponotus sp 16 Subordinate 1 0 Formicinae Camponotus sp 17 Subordinate 5 0

168 Formicinae Melophorus c.f. Hot 79 23 anderseni Formicinae Melophorus cf. Hot 1945 0 aeneovirens Formicinae Melophorus c.f. fieldi Hot 19 4900 Formicinae Melophorus c.f. group C Hot 442 0 Formicinae Melophorus c.f. group F Hot 5 432 Formicinae Melophorus c.f. group H Hot 412 77 Formicinae Melophorus c.f. pillipes Hot 246 1 Formicinae Melophorus c.f. turneri Hot 320 413 Formicinae Melophorus c.f. bagoti Hot 62 0 Formicinae Melophorus c.f. wheeleri Hot 60 927 Formicinae Melophorus sp 7 Hot 877 0 Formicinae Melophorus sp 9 Hot 192 102 Formicinae Notoncus capitatus Cold 9 0 Formicinae Notoncus ectatommoides Cold 13 59 Formicinae Opisthopsis rufithorax Subordinate 4 0 Formicinae Nylanderia sp 1 Opportunist 41 0 Formicinae Nylanderia sp 2 Opportunist 3 0 Formicinae Polyrhachis sp 1 Subordinate 8 0 Formicinae Polyrhachis sp 2 Subordinate 5 0 Formicinae Polyrachis sp 3 Subordinate 1 0 Formicinae Stigmacros Cold 60 0 (Campostigmacros) sp 1 Formicinae Stigmacros sp 2 Cold 33 1 Formicinae Stigmacros sp 3 Cold 21 1 Formicinae Stigmacros sp 4 Cold 12 0 Formicinae Stigmacros sp 5 Cold 9 0 Myrmecinae Myrmecia sp 1 Specialist 2 0 Myrmicinae Aphaenogaster longiceps Opportunist 3 0 Myrmicinae Cardiocondyla sp 1 Generalist 16 12 Myrmicinae Carebara sp 1 Cryptic 1 0 Myrmicinae Colobstruma bioconvexa Specialist 1 0 Myrmicinae Crematogaster sp 1 Generalist 46 6 Myrmicinae Crematogaster sp 2 Generalist 1 0 Myrmicinae Crematogaster sp 3 Generalist 3 0 Myrmicinae Meranoplus sp 1 Hot 299 0 Myrmicinae Meranoplus sp 2 Hot 69 3 Myrmicinae Meranoplus sp 3 Hot 29 0 Myrmicinae Meranoplus sp 4 Hot 13 1 Myrmicinae Meranoplus sp 5 Hot 24 0 Myrmicinae Monomorium centrale Hot 0 3517 Myrmicinae Monomorium euryodon Cryptic 1 642 Myrmicinae Monomorium fieldi Generalist 208 567 Myrmicinae Monomorium rothsteini Generalist 51 0 Myrmicinae Monomorium sordidum Generalist 2293 32732

169 Myrmicinae Monomorium sp 1 Generalist 69 1529 Myrmicinae Monomorium cf. laeve Generalist 5 1301 Myrmicinae Monomorium sp 4 Generalist 0 8271 Myrmicinae Monomorium sp 10 Generalist 1 11 Myrmicinae Monomorium sp 12 Generalist 0 2599 Myrmicinae Monomorium sydnyense Generalist 492 4165 Myrmicinae Pheidole antipodum Hot 3 31057 Myrmicinae Pheidole sp 1 Generalist 34 633 Myrmicinae Pheidole sp 2 Generalist 7 0 Myrmicinae Pheidole sp 3 Generalist 45 0 Myrmicinae Pheidole sp 4 Generalist 8 48 Myrmicinae Pheidole sp 5 Generalist 73 11473 Myrmicinae Pheidole sp 6 Generalist 77 206 Myrmicinae Pheidole sp 7 Generalist 615 1213 Myrmicinae Podomyrma adelaidae Cold 5 0 Myrmicinae Solenopsis cf. belisaurus Cryptic 0 8555 Myrmicinae Solenopsis cf. clarki Cryptic 0 72469 Myrmicinae Solenopsis sp 1 Cryptic 0 3929 Myrmicinae Solenopsis sp 3 Cryptic 2 600 Myrmicinae Tetramorium sp 1 Opportunist 17 4 Myrmicinae Tetramorium sp 2 Opportunist 45 2 Myrmicinae Tetramorium sp 3 Opportunist 80 3 Myrmicinae Tetramorium sp 5 Opportunist 11 0 Ponerinae Anochetus renatae Specialist 8 0 Ponerinae Brachyponera lutea Cryptic 3 2385 Ponerinae Heteroponera sp 1 Cold 1 0 Ponerinae Heteroponera sp 2 Cold 0 1 Ponerinae Odontomachus ruficeps Opportunist 4 0 Ponerinae Rhytidoponera metallica Opportunist 2605 2300 Ponerinae Rhytidoponera sp 1 Opportunist 776 4 Ponerinae Rhytidoponera sp 2 Opportunist 439 0

170

Appendix F

Generalized linear models for aboveground, belowground, and functional group ant species richness for grazing history, grazing intensity, and their interaction. Int. = model intercept; SE = standard error. Bold is a significant measure.

Subject and Model Int. Estimate SE z-score P-value df Aboveground History 3.079 0.093 0.043 2.11 0.035 58 Intensity 3.079 -0.052 0.037 1.42 0.155 58 History*Intensity 3.079 -0.030 0.043 0.7 0.484 56 Belowground History 1.926 0.076 0.085 0.899 0.369 58 Intensity 1.926 -0.034 0.051 0.668 0.504 58 History*Intensity 1.926 -0.014 0.062 0.227 0.821 56 Dominant Dolichoderinae History 1.230 0.695 0.092 0.757 0.449 58 Intensity 1.215 -0.176 0.065 2.687 0.007 58 History*Intensity 1.214 -0.061 0.081 0.755 0.450 56 Generalized Myrmicinae History 1.364 0.133 0.079 1.676 0.094 58 Intensity 1.363 -0.016 0.066 0.246 0.806 58 History*Intensity 1.364 -0.064 0.079 0.809 0.418 56 Hot Climate Specialist History 1.499 0.200 0.073 2.743 0.006 58 Intensity 1.495 -0.133 0.058 2.305 0.021 58 History*Intensity 1.490 0.008 0.071 -0.118 0.906 56 Opportunist History 1.510 -0.100 0.072 -1.375 0.169 58 Intensity 1.509 0.088 0.061 -1.440 0.150 58 History*Intensity 1.504 -0.073 0.075 0.970 0.332 56 Subordinate Camponotini History 1.352 0.231 0.079 2.942 0.003 58 Intensity 1.353 -0.101 0.062 1.619 0.105 58 History*Intensity 1.345 0.059 0.077 -0.077 0.441 56

171 Appendix G

Appendix G. The first two dimensions of the MDS biplot for aboveground and belowground ant communities in relation to three levels of historic grazing.

172